Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/12/16/rob-reiner-trump-my-brother-also-murdered-my-mother.html

I posted the following on my Fediverse (via Mastodon) account.
I’m reposting the whole seven posts here as written there, but I hope folks
will take a
look at that thread as folks are engaging in conversation over there
that might be worth reading if what I have to say interests you.
(The remainder of the post is the same that can be found in the Fediverse
posts linked throughout.)

I
suppose Fediverse
isn’t the place people are discussing Rob Reiner. But after 36 hours of deliberating whether to say anything, I feel compelled. This thread will be long,but I start w/ most important part:

It’s an “open secret” in the FOSS community that in March 2017 my brother
murdered our mother. About 3k ppl/year in USA have this experience, so it’s
a statistical reality that someone else in FOSS experienced similar. If so,
you’re welcome in my PMs to discuss if you need support… (1/7)

… Traumatic loss due to murder is different than losing your
grandparent/parent of age-related ailments (& is even different than
losing a young person to a disease like cancer). The “a fellow family
member did it” brings permanent surrealism to your daily life. Nothing good
in your life that comes later is ever all that good. I know from direct
experience this is what Rob Reiner’s family now faces. It’s chaos; it
divides families forever: dysfunctional family takes on a new “expert”
level… (2/7)

…as one example: my family was immediately divided about punishment. Some
of my mother’s relatives wanted prosecution to seek death penalty. I knew
that my brother was mentally ill enough that jail or prison *would* get him
killed in a prison dispute eventually,so I met clandestinely w/my brother’s
public defender (during funeral planning!) to get him moved to a criminal
mental health facility instead of a regular prison. If they read this,
it’ll first time my family will find out I did that…(3/7)

…Trump’s political rise (for me) links up: 5 weeks into Trump’s 1ˢᵗ term, my brother murdered my mother.
My (then 33yr-old) brother was severely mentally ill from birth — yet escalated to murder only then. IMO, it wasn’t coincidence. My brother left voicemail approximately 5 hours before the murder stating his intent to murder & described an elaborate political delusion as the impetus.

∃ unintended & dangerous consequences of inflammatory political rhetoric on
the mental ill!…(4/7)

…I’m compelled to speak publicly — for first time ≈10 yrs after the murder —
precisely b/c of Trump’s response.

Trump endorsed the idea that those who oppose him encourage their own
murder from the mentally ill. Indeed, he said that those who oppose him are
*themselves causing* mental illnesses in those around them, & that his
political opponents should *expect* violence from their family members (who
were apparently driven to mental illness from your opposition to
Trump!)… (5/7)

…Trump’s actual words:

Rob Reiner, tortured & struggling,but once…talented movie director &
comedy star, has passed away, together w/ his wife…due to the anger he
caused others through his massive, unyielding, & incurable affliction w/ a
mind crippling disease known as TRUMP DERANGEMENT SYNDROME…He was known to
have driven people CRAZY by his raging obsession of…Trump, w/ his obvious
paranoia reaching new heights as [my] Administration surpassed all goals
and expectations of greatness…

(6/7)

My family became ultra-pro-Trump after my mom’s murder. My mom hated
politics: she was annoyed *both* if I touted my social democratic politics &
if my dad & his family stated their crypto-fascist views.

Every death leaves a hole in a community’s political fabric. 9+ years out,
I’m ostracized from my family b/c I’m anti-Trump.

Trump stated perhaps what my family felt but didn’t say: those who don’t
support Trump are at fault when those who fail to support Trump are
murdered. (7/7)

[ Finally, I want to also quote this one reply I also posted in the same
thread:
I ask everyone, now that I’ve stated this public, that I *know* you’re going to want to search the Internet for it, & you will find a lot. Please, please, keep in mind that the Police Department & others basically lied to the public about some of the facts of the case. I seriously considered suing them for it, but ultimately it wasn’t worth my time. But, please everyone ask me if you are curious about any of the truth of the details of the crime & its aftermath …

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/12/16/rob-reiner-trump-my-brother-also-murdered-my-mother.html

I posted the following on my Fediverse (via Mastodon) account.
I’m reposting the whole seven posts here as written there, but I hope folks
will take a
look at that thread as folks are engaging in conversation over there
that might be worth reading if what I have to say interests you.
(The remainder of the post is the same that can be found in the Fediverse
posts linked throughout.)

I
suppose Fediverse
isn’t the place people are discussing Rob Reiner. But after 36 hours of deliberating whether to say anything, I feel compelled. This thread will be long,but I start w/ most important part:

It’s an “open secret” in the FOSS community that in March 2017 my brother
murdered our mother. About 3k ppl/year in USA have this experience, so it’s
a statistical reality that someone else in FOSS experienced similar. If so,
you’re welcome in my PMs to discuss if you need support… (1/7)

… Traumatic loss due to murder is different than losing your
grandparent/parent of age-related ailments (& is even different than
losing a young person to a disease like cancer). The “a fellow family
member did it” brings permanent surrealism to your daily life. Nothing good
in your life that comes later is ever all that good. I know from direct
experience this is what Rob Reiner’s family now faces. It’s chaos; it
divides families forever: dysfunctional family takes on a new “expert”
level… (2/7)

…as one example: my family was immediately divided about punishment. Some
of my mother’s relatives wanted prosecution to seek death penalty. I knew
that my brother was mentally ill enough that jail or prison *would* get him
killed in a prison dispute eventually,so I met clandestinely w/my brother’s
public defender (during funeral planning!) to get him moved to a criminal
mental health facility instead of a regular prison. If they read this,
it’ll first time my family will find out I did that…(3/7)

…Trump’s political rise (for me) links up: 5 weeks into Trump’s 1ˢᵗ term, my brother murdered my mother.
My (then 33yr-old) brother was severely mentally ill from birth — yet escalated to murder only then. IMO, it wasn’t coincidence. My brother left voicemail approximately 5 hours before the murder stating his intent to murder & described an elaborate political delusion as the impetus.

∃ unintended & dangerous consequences of inflammatory political rhetoric on
the mental ill!…(4/7)

…I’m compelled to speak publicly — for first time ≈10 yrs after the murder —
precisely b/c of Trump’s response.

Trump endorsed the idea that those who oppose him encourage their own
murder from the mentally ill. Indeed, he said that those who oppose him are
*themselves causing* mental illnesses in those around them, & that his
political opponents should *expect* violence from their family members (who
were apparently driven to mental illness from your opposition to
Trump!)… (5/7)

…Trump’s actual words:

Rob Reiner, tortured & struggling,but once…talented movie director &
comedy star, has passed away, together w/ his wife…due to the anger he
caused others through his massive, unyielding, & incurable affliction w/ a
mind crippling disease known as TRUMP DERANGEMENT SYNDROME…He was known to
have driven people CRAZY by his raging obsession of…Trump, w/ his obvious
paranoia reaching new heights as [my] Administration surpassed all goals
and expectations of greatness…

(6/7)

My family became ultra-pro-Trump after my mom’s murder. My mom hated
politics: she was annoyed *both* if I touted my social democratic politics &
if my dad & his family stated their crypto-fascist views.

Every death leaves a hole in a community’s political fabric. 9+ years out,
I’m ostracized from my family b/c I’m anti-Trump.

Trump stated perhaps what my family felt but didn’t say: those who don’t
support Trump are at fault when those who fail to support Trump are
murdered. (7/7)

[ Finally, I want to also quote this one reply I also posted in the same
thread:
I ask everyone, now that I’ve stated this public, that I *know* you’re going to want to search the Internet for it, & you will find a lot. Please, please, keep in mind that the Police Department & others basically lied to the public about some of the facts of the case. I seriously considered suing them for it, but ultimately it wasn’t worth my time. But, please everyone ask me if you are curious about any of the truth of the details of the crime & its aftermath …

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/12/16/rob-reiner-trump-my-brother-also-murdered-my-mother.html

I posted the following on my Fediverse (via Mastodon) account.
I’m reposting the whole seven posts here as written there, but I hope folks
will take a
look at that thread as folks are engaging in conversation over there
that might be worth reading if what I have to say interests you.
(The remainder of the post is the same that can be found in the Fediverse
posts linked throughout.)

I
suppose Fediverse
isn’t the place people are discussing Rob Reiner. But after 36 hours of deliberating whether to say anything, I feel compelled. This thread will be long,but I start w/ most important part:

It’s an “open secret” in the FOSS community that in March 2017 my brother
murdered our mother. About 3k ppl/year in USA have this experience, so it’s
a statistical reality that someone else in FOSS experienced similar. If so,
you’re welcome in my PMs to discuss if you need support… (1/7)

… Traumatic loss due to murder is different than losing your
grandparent/parent of age-related ailments (& is even different than
losing a young person to a disease like cancer). The “a fellow family
member did it” brings permanent surrealism to your daily life. Nothing good
in your life that comes later is ever all that good. I know from direct
experience this is what Rob Reiner’s family now faces. It’s chaos; it
divides families forever: dysfunctional family takes on a new “expert”
level… (2/7)

…as one example: my family was immediately divided about punishment. Some
of my mother’s relatives wanted prosecution to seek death penalty. I knew
that my brother was mentally ill enough that jail or prison *would* get him
killed in a prison dispute eventually,so I met clandestinely w/my brother’s
public defender (during funeral planning!) to get him moved to a criminal
mental health facility instead of a regular prison. If they read this,
it’ll first time my family will find out I did that…(3/7)

…Trump’s political rise (for me) links up: 5 weeks into Trump’s 1ˢᵗ term, my brother murdered my mother.
My (then 33yr-old) brother was severely mentally ill from birth — yet escalated to murder only then. IMO, it wasn’t coincidence. My brother left voicemail approximately 5 hours before the murder stating his intent to murder & described an elaborate political delusion as the impetus.

∃ unintended & dangerous consequences of inflammatory political rhetoric on
the mental ill!…(4/7)

…I’m compelled to speak publicly — for first time ≈10 yrs after the murder —
precisely b/c of Trump’s response.

Trump endorsed the idea that those who oppose him encourage their own
murder from the mentally ill. Indeed, he said that those who oppose him are
*themselves causing* mental illnesses in those around them, & that his
political opponents should *expect* violence from their family members (who
were apparently driven to mental illness from your opposition to
Trump!)… (5/7)

…Trump’s actual words:

Rob Reiner, tortured & struggling,but once…talented movie director &
comedy star, has passed away, together w/ his wife…due to the anger he
caused others through his massive, unyielding, & incurable affliction w/ a
mind crippling disease known as TRUMP DERANGEMENT SYNDROME…He was known to
have driven people CRAZY by his raging obsession of…Trump, w/ his obvious
paranoia reaching new heights as [my] Administration surpassed all goals
and expectations of greatness…

(6/7)

My family became ultra-pro-Trump after my mom’s murder. My mom hated
politics: she was annoyed *both* if I touted my social democratic politics &
if my dad & his family stated their crypto-fascist views.

Every death leaves a hole in a community’s political fabric. 9+ years out,
I’m ostracized from my family b/c I’m anti-Trump.

Trump stated perhaps what my family felt but didn’t say: those who don’t
support Trump are at fault when those who fail to support Trump are
murdered. (7/7)

[ Finally, I want to also quote this one reply I also posted in the same
thread:
I ask everyone, now that I’ve stated this public, that I *know* you’re going to want to search the Internet for it, & you will find a lot. Please, please, keep in mind that the Police Department & others basically lied to the public about some of the facts of the case. I seriously considered suing them for it, but ultimately it wasn’t worth my time. But, please everyone ask me if you are curious about any of the truth of the details of the crime & its aftermath …

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/12/16/rob-reiner-trump-my-brother-also-murdered-my-mother.html

I posted the following on my Fediverse (via Mastodon) account.
I’m reposting the whole seven posts here as written there, but I hope folks
will take a
look at that thread as folks are engaging in conversation over there
that might be worth reading if what I have to say interests you.
(The remainder of the post is the same that can be found in the Fediverse
posts linked throughout.)

I
suppose Fediverse
isn’t the place people are discussing Rob Reiner. But after 36 hours of deliberating whether to say anything, I feel compelled. This thread will be long,but I start w/ most important part:

It’s an “open secret” in the FOSS community that in March 2017 my brother
murdered our mother. About 3k ppl/year in USA have this experience, so it’s
a statistical reality that someone else in FOSS experienced similar. If so,
you’re welcome in my PMs to discuss if you need support… (1/7)

… Traumatic loss due to murder is different than losing your
grandparent/parent of age-related ailments (& is even different than
losing a young person to a disease like cancer). The “a fellow family
member did it” brings permanent surrealism to your daily life. Nothing good
in your life that comes later is ever all that good. I know from direct
experience this is what Rob Reiner’s family now faces. It’s chaos; it
divides families forever: dysfunctional family takes on a new “expert”
level… (2/7)

…as one example: my family was immediately divided about punishment. Some
of my mother’s relatives wanted prosecution to seek death penalty. I knew
that my brother was mentally ill enough that jail or prison *would* get him
killed in a prison dispute eventually,so I met clandestinely w/my brother’s
public defender (during funeral planning!) to get him moved to a criminal
mental health facility instead of a regular prison. If they read this,
it’ll first time my family will find out I did that…(3/7)

…Trump’s political rise (for me) links up: 5 weeks into Trump’s 1ˢᵗ term, my brother murdered my mother.
My (then 33yr-old) brother was severely mentally ill from birth — yet escalated to murder only then. IMO, it wasn’t coincidence. My brother left voicemail approximately 5 hours before the murder stating his intent to murder & described an elaborate political delusion as the impetus.

∃ unintended & dangerous consequences of inflammatory political rhetoric on
the mental ill!…(4/7)

…I’m compelled to speak publicly — for first time ≈10 yrs after the murder —
precisely b/c of Trump’s response.

Trump endorsed the idea that those who oppose him encourage their own
murder from the mentally ill. Indeed, he said that those who oppose him are
*themselves causing* mental illnesses in those around them, & that his
political opponents should *expect* violence from their family members (who
were apparently driven to mental illness from your opposition to
Trump!)… (5/7)

…Trump’s actual words:

Rob Reiner, tortured & struggling,but once…talented movie director &
comedy star, has passed away, together w/ his wife…due to the anger he
caused others through his massive, unyielding, & incurable affliction w/ a
mind crippling disease known as TRUMP DERANGEMENT SYNDROME…He was known to
have driven people CRAZY by his raging obsession of…Trump, w/ his obvious
paranoia reaching new heights as [my] Administration surpassed all goals
and expectations of greatness…

(6/7)

My family became ultra-pro-Trump after my mom’s murder. My mom hated
politics: she was annoyed *both* if I touted my social democratic politics &
if my dad & his family stated their crypto-fascist views.

Every death leaves a hole in a community’s political fabric. 9+ years out,
I’m ostracized from my family b/c I’m anti-Trump.

Trump stated perhaps what my family felt but didn’t say: those who don’t
support Trump are at fault when those who fail to support Trump are
murdered. (7/7)

[ Finally, I want to also quote this one reply I also posted in the same
thread:
I ask everyone, now that I’ve stated this public, that I *know* you’re going to want to search the Internet for it, & you will find a lot. Please, please, keep in mind that the Police Department & others basically lied to the public about some of the facts of the case. I seriously considered suing them for it, but ultimately it wasn’t worth my time. But, please everyone ask me if you are curious about any of the truth of the details of the crime & its aftermath …

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/11/06/juggluco-foss-continuous-glucose-montior-diabetes.html

[ The below is a cross-post of an article that I published on my blog
at Software Freedom Conservancy. ]

Our member project representatives and others who collaborate with
SFC on projects
know that I’ve been on part-time medical leave this year. As I recently announced publicly on the Fediverse, I was diagnosed in March 2025 with early-stage Type
2 Diabetes. I had no idea that that the diagnosis would become a
software freedom and users’ rights endeavor.

After the diagnosis, my doctor suggested immediately that I see the diabetes nurse-practitioner
specialist in their practice. It took some time get an appointment with him,
so I saw him first in mid-April 2025.

I walked into the office, sat down, and within minutes the specialist
asked me to “take out your phone and install the Freestyle Libre app
from Abbott”. This is the first (but, will probably not be the only) time a medical practitioner
asked me to install proprietary software as the first step of
treatment.

The specialist told me that in his experience, even early-stage diabetics
like me should use a Continuous Glucose Monitor (CGM). CGM’s
are an amazing (relatively) recent invention that allows diabetics to
sample their blood sugar level constantly. As we software developers and
engineers know: great things happen when your diagnostic readout is as low
latency as possible. CGMs lower the latency of readouts from 3–4
times a day to every five minutes. For example, diabetics can see
what foods are most likely to cause blood sugar spikes for them
personally. CGMs put patients on a path to manage this chronic condition
well.

But, the devices themselves, and the (default) apps that control them are
hopelessly proprietary. Fortunately, this was (obviously) not my first time
explaining
FOSS from first
principles. So, I read through the license and terms and conditions of the
ironically named “Freestyle Libre” app, and pointed out to the
specialist how patient-unfriendly the terms were. For example, Abbott (the
manufacturer of my CGM) reserves the right to collect your data
(anonymously of course, to “improve the product”). They also
require patients to agree that if they take any action to reverse engineer,
modify, or otherwise do the normal things our community does with
software, the patient must agree that such actions “constitute
immediate, irreparable harm to Abbott, its affiliates, and/or its
licensors”. I briefly explained to the specialist that I could not
possibly agree. I began in real-time (still sitting with the specialist) a
search for a FOSS solution.

As I was searching, the specialist said: “Oh, I don’t use any of it
myself, but I think I’ve heard of this ‘open source’ thing
— there is a program called xDrip+ that is for insulin-dependent
diabetics that I’ve heard of and some patients report it is quite
good”.

While I’m (luckily) very far from insulin-dependency, I eventually found
the FOSS Android app called
Juggluco (a
portmanteau for “Juggle glucose”). I asked the specialist to
give me the prescription and I’d try Juggluco to see if it would work.

CGM‘s are very small
and their firmware is (by obvious necessity) quite simple. As such, their
interfaces are standard. CGM’s are activated with Near Field Communication
(NFC) — available on even quite old Android devices.
The Android device sends a simple integer identifier via NFC that activates
the CGM. Once activated — and through the 15-day life of the device
— the device responds via Bluetooth with the patient’s current
glucose reading to any device presenting that integer.

Fortunately, I quickly discovered that the FOSS community was already
“on this”. The NFC activation worked just fine, even on the
recently updated “Freestyle Libre 3+”. After
the sixty minute calibration period, I had a continuous readout in Juggluco.

CGM‘s lower latency
feedback enables diabetics to have more control of their illness
management. one example among many: the patient can see (in real time)
what foods most often cause blood sugar spikes for
them personally. Diabetes hits everyone differently; data allows
everyone to manage their own chronic condition better.

My personal story with Juggluco will continue — as I hope (although
not until after FOSDEM 2026 😆) to become an upstream contributor to
Juggluco. Most importantly, I hope to help the app appear in F-Droid. (I
must currently side-load or use Aurora Store to make it work on
LineageOS.)

Fitting with the history that many projects that interact with proprietary
technology must so often live through, Juggluco has
faced surreptitious
removal from Google’s Play Store. Abbott even accused Juggluco of
using their proprietary libraries and encryption methods, but the so-called
“encryption method” is literally sending an single integer as
part of NFC activation.

While Abbott backed off, this is another example of why the movement of
patients taking control of the technology remains
essential. FOSS
fits perfectly with this goal. Software freedom gives control of
technology to those who actually rely on it — rather than for-profit
medical equipment manufacturers.

When I returned to my specialist for a follow-up, we reviewed the data and
graphs that I produced with Juggluco. I, of course, have never installed,
used, or even agreed to Abbott’s licenses and terms, so I have never seen
what the Abbott app does. I was thus surprised when I showed my specialist
Juggluco’s summary graphs. He excitedly told me “this is much better
reporting than the Abbott app gives you!”. We all know that
sometimes proprietary software has better and more features than the FOSS
equivalent, so it’s a particularly great success when our community efforts
outdoes a wealthy 200 billion-dollar megacorp on software features!

Please do watch SFC’s site in 2026 for more posts about my ongoing work
with Juggluco, and
please give generously as an
SFC Sustainer to help this and our other work continue in 2026!

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/11/06/juggluco-foss-continuous-glucose-montior-diabetes.html

[ The below is a cross-post of an article that I published on my blog
at Software Freedom Conservancy. ]

Our member project representatives and others who collaborate with
SFC on projects
know that I’ve been on part-time medical leave this year. As I recently announced publicly on the Fediverse, I was diagnosed in March 2025 with early-stage Type
2 Diabetes. I had no idea that that the diagnosis would become a
software freedom and users’ rights endeavor.

After the diagnosis, my doctor suggested immediately that I see the diabetes nurse-practitioner
specialist in their practice. It took some time get an appointment with him,
so I saw him first in mid-April 2025.

I walked into the office, sat down, and within minutes the specialist
asked me to “take out your phone and install the Freestyle Libre app
from Abbott”. This is the first (but, will probably not be the only) time a medical practitioner
asked me to install proprietary software as the first step of
treatment.

The specialist told me that in his experience, even early-stage diabetics
like me should use a Continuous Glucose Monitor (CGM). CGM’s
are an amazing (relatively) recent invention that allows diabetics to
sample their blood sugar level constantly. As we software developers and
engineers know: great things happen when your diagnostic readout is as low
latency as possible. CGMs lower the latency of readouts from 3–4
times a day to every five minutes. For example, diabetics can see
what foods are most likely to cause blood sugar spikes for them
personally. CGMs put patients on a path to manage this chronic condition
well.

But, the devices themselves, and the (default) apps that control them are
hopelessly proprietary. Fortunately, this was (obviously) not my first time
explaining
FOSS from first
principles. So, I read through the license and terms and conditions of the
ironically named “Freestyle Libre” app, and pointed out to the
specialist how patient-unfriendly the terms were. For example, Abbott (the
manufacturer of my CGM) reserves the right to collect your data
(anonymously of course, to “improve the product”). They also
require patients to agree that if they take any action to reverse engineer,
modify, or otherwise do the normal things our community does with
software, the patient must agree that such actions “constitute
immediate, irreparable harm to Abbott, its affiliates, and/or its
licensors”. I briefly explained to the specialist that I could not
possibly agree. I began in real-time (still sitting with the specialist) a
search for a FOSS solution.

As I was searching, the specialist said: “Oh, I don’t use any of it
myself, but I think I’ve heard of this ‘open source’ thing
— there is a program called xDrip+ that is for insulin-dependent
diabetics that I’ve heard of and some patients report it is quite
good”.

While I’m (luckily) very far from insulin-dependency, I eventually found
the FOSS Android app called
Juggluco (a
portmanteau for “Juggle glucose”). I asked the specialist to
give me the prescription and I’d try Juggluco to see if it would work.

CGM‘s are very small
and their firmware is (by obvious necessity) quite simple. As such, their
interfaces are standard. CGM’s are activated with Near Field Communication
(NFC) — available on even quite old Android devices.
The Android device sends a simple integer identifier via NFC that activates
the CGM. Once activated — and through the 15-day life of the device
— the device responds via Bluetooth with the patient’s current
glucose reading to any device presenting that integer.

Fortunately, I quickly discovered that the FOSS community was already
“on this”. The NFC activation worked just fine, even on the
recently updated “Freestyle Libre 3+”. After
the sixty minute calibration period, I had a continuous readout in Juggluco.

CGM‘s lower latency
feedback enables diabetics to have more control of their illness
management. one example among many: the patient can see (in real time)
what foods most often cause blood sugar spikes for
them personally. Diabetes hits everyone differently; data allows
everyone to manage their own chronic condition better.

My personal story with Juggluco will continue — as I hope (although
not until after FOSDEM 2026 😆) to become an upstream contributor to
Juggluco. Most importantly, I hope to help the app appear in F-Droid. (I
must currently side-load or use Aurora Store to make it work on
LineageOS.)

Fitting with the history that many projects that interact with proprietary
technology must so often live through, Juggluco has
faced surreptitious
removal from Google’s Play Store. Abbott even accused Juggluco of
using their proprietary libraries and encryption methods, but the so-called
“encryption method” is literally sending an single integer as
part of NFC activation.

While Abbott backed off, this is another example of why the movement of
patients taking control of the technology remains
essential. FOSS
fits perfectly with this goal. Software freedom gives control of
technology to those who actually rely on it — rather than for-profit
medical equipment manufacturers.

When I returned to my specialist for a follow-up, we reviewed the data and
graphs that I produced with Juggluco. I, of course, have never installed,
used, or even agreed to Abbott’s licenses and terms, so I have never seen
what the Abbott app does. I was thus surprised when I showed my specialist
Juggluco’s summary graphs. He excitedly told me “this is much better
reporting than the Abbott app gives you!”. We all know that
sometimes proprietary software has better and more features than the FOSS
equivalent, so it’s a particularly great success when our community efforts
outdoes a wealthy 200 billion-dollar megacorp on software features!

Please do watch SFC’s site in 2026 for more posts about my ongoing work
with Juggluco, and
please give generously as an
SFC Sustainer to help this and our other work continue in 2026!

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/11/06/juggluco-foss-continuous-glucose-montior-diabetes.html

[ The below is a cross-post of an article that I published on my blog
at Software Freedom Conservancy. ]

Our member project representatives and others who collaborate with
SFC on projects
know that I’ve been on part-time medical leave this year. As I recently announced publicly on the Fediverse, I was diagnosed in March 2025 with early-stage Type
2 Diabetes. I had no idea that that the diagnosis would become a
software freedom and users’ rights endeavor.

After the diagnosis, my doctor suggested immediately that I see the diabetes nurse-practitioner
specialist in their practice. It took some time get an appointment with him,
so I saw him first in mid-April 2025.

I walked into the office, sat down, and within minutes the specialist
asked me to “take out your phone and install the Freestyle Libre app
from Abbott”. This is the first (but, will probably not be the only) time a medical practitioner
asked me to install proprietary software as the first step of
treatment.

The specialist told me that in his experience, even early-stage diabetics
like me should use a Continuous Glucose Monitor (CGM). CGM’s
are an amazing (relatively) recent invention that allows diabetics to
sample their blood sugar level constantly. As we software developers and
engineers know: great things happen when your diagnostic readout is as low
latency as possible. CGMs lower the latency of readouts from 3–4
times a day to every five minutes. For example, diabetics can see
what foods are most likely to cause blood sugar spikes for them
personally. CGMs put patients on a path to manage this chronic condition
well.

But, the devices themselves, and the (default) apps that control them are
hopelessly proprietary. Fortunately, this was (obviously) not my first time
explaining
FOSS from first
principles. So, I read through the license and terms and conditions of the
ironically named “Freestyle Libre” app, and pointed out to the
specialist how patient-unfriendly the terms were. For example, Abbott (the
manufacturer of my CGM) reserves the right to collect your data
(anonymously of course, to “improve the product”). They also
require patients to agree that if they take any action to reverse engineer,
modify, or otherwise do the normal things our community does with
software, the patient must agree that such actions “constitute
immediate, irreparable harm to Abbott, its affiliates, and/or its
licensors”. I briefly explained to the specialist that I could not
possibly agree. I began in real-time (still sitting with the specialist) a
search for a FOSS solution.

As I was searching, the specialist said: “Oh, I don’t use any of it
myself, but I think I’ve heard of this ‘open source’ thing
— there is a program called xDrip+ that is for insulin-dependent
diabetics that I’ve heard of and some patients report it is quite
good”.

While I’m (luckily) very far from insulin-dependency, I eventually found
the FOSS Android app called
Juggluco (a
portmanteau for “Juggle glucose”). I asked the specialist to
give me the prescription and I’d try Juggluco to see if it would work.

CGM‘s are very small
and their firmware is (by obvious necessity) quite simple. As such, their
interfaces are standard. CGM’s are activated with Near Field Communication
(NFC) — available on even quite old Android devices.
The Android device sends a simple integer identifier via NFC that activates
the CGM. Once activated — and through the 15-day life of the device
— the device responds via Bluetooth with the patient’s current
glucose reading to any device presenting that integer.

Fortunately, I quickly discovered that the FOSS community was already
“on this”. The NFC activation worked just fine, even on the
recently updated “Freestyle Libre 3+”. After
the sixty minute calibration period, I had a continuous readout in Juggluco.

CGM‘s lower latency
feedback enables diabetics to have more control of their illness
management. one example among many: the patient can see (in real time)
what foods most often cause blood sugar spikes for
them personally. Diabetes hits everyone differently; data allows
everyone to manage their own chronic condition better.

My personal story with Juggluco will continue — as I hope (although
not until after FOSDEM 2026 😆) to become an upstream contributor to
Juggluco. Most importantly, I hope to help the app appear in F-Droid. (I
must currently side-load or use Aurora Store to make it work on
LineageOS.)

Fitting with the history that many projects that interact with proprietary
technology must so often live through, Juggluco has
faced surreptitious
removal from Google’s Play Store. Abbott even accused Juggluco of
using their proprietary libraries and encryption methods, but the so-called
“encryption method” is literally sending an single integer as
part of NFC activation.

While Abbott backed off, this is another example of why the movement of
patients taking control of the technology remains
essential. FOSS
fits perfectly with this goal. Software freedom gives control of
technology to those who actually rely on it — rather than for-profit
medical equipment manufacturers.

When I returned to my specialist for a follow-up, we reviewed the data and
graphs that I produced with Juggluco. I, of course, have never installed,
used, or even agreed to Abbott’s licenses and terms, so I have never seen
what the Abbott app does. I was thus surprised when I showed my specialist
Juggluco’s summary graphs. He excitedly told me “this is much better
reporting than the Abbott app gives you!”. We all know that
sometimes proprietary software has better and more features than the FOSS
equivalent, so it’s a particularly great success when our community efforts
outdoes a wealthy 200 billion-dollar megacorp on software features!

Please do watch SFC’s site in 2026 for more posts about my ongoing work
with Juggluco, and
please give generously as an
SFC Sustainer to help this and our other work continue in 2026!

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/11/06/juggluco-foss-continuous-glucose-montior-diabetes.html

[ The below is a cross-post of an article that I published on my blog
at Software Freedom Conservancy. ]

Our member project representatives and others who collaborate with
SFC on projects
know that I’ve been on part-time medical leave this year. As I recently announced publicly on the Fediverse, I was diagnosed in March 2025 with early-stage Type
2 Diabetes. I had no idea that that the diagnosis would become a
software freedom and users’ rights endeavor.

After the diagnosis, my doctor suggested immediately that I see the diabetes nurse-practitioner
specialist in their practice. It took some time get an appointment with him,
so I saw him first in mid-April 2025.

I walked into the office, sat down, and within minutes the specialist
asked me to “take out your phone and install the Freestyle Libre app
from Abbott”. This is the first (but, will probably not be the only) time a medical practitioner
asked me to install proprietary software as the first step of
treatment.

The specialist told me that in his experience, even early-stage diabetics
like me should use a Continuous Glucose Monitor (CGM). CGM’s
are an amazing (relatively) recent invention that allows diabetics to
sample their blood sugar level constantly. As we software developers and
engineers know: great things happen when your diagnostic readout is as low
latency as possible. CGMs lower the latency of readouts from 3–4
times a day to every five minutes. For example, diabetics can see
what foods are most likely to cause blood sugar spikes for them
personally. CGMs put patients on a path to manage this chronic condition
well.

But, the devices themselves, and the (default) apps that control them are
hopelessly proprietary. Fortunately, this was (obviously) not my first time
explaining
FOSS from first
principles. So, I read through the license and terms and conditions of the
ironically named “Freestyle Libre” app, and pointed out to the
specialist how patient-unfriendly the terms were. For example, Abbott (the
manufacturer of my CGM) reserves the right to collect your data
(anonymously of course, to “improve the product”). They also
require patients to agree that if they take any action to reverse engineer,
modify, or otherwise do the normal things our community does with
software, the patient must agree that such actions “constitute
immediate, irreparable harm to Abbott, its affiliates, and/or its
licensors”. I briefly explained to the specialist that I could not
possibly agree. I began in real-time (still sitting with the specialist) a
search for a FOSS solution.

As I was searching, the specialist said: “Oh, I don’t use any of it
myself, but I think I’ve heard of this ‘open source’ thing
— there is a program called xDrip+ that is for insulin-dependent
diabetics that I’ve heard of and some patients report it is quite
good”.

While I’m (luckily) very far from insulin-dependency, I eventually found
the FOSS Android app called
Juggluco (a
portmanteau for “Juggle glucose”). I asked the specialist to
give me the prescription and I’d try Juggluco to see if it would work.

CGM‘s are very small
and their firmware is (by obvious necessity) quite simple. As such, their
interfaces are standard. CGM’s are activated with Near Field Communication
(NFC) — available on even quite old Android devices.
The Android device sends a simple integer identifier via NFC that activates
the CGM. Once activated — and through the 15-day life of the device
— the device responds via Bluetooth with the patient’s current
glucose reading to any device presenting that integer.

Fortunately, I quickly discovered that the FOSS community was already
“on this”. The NFC activation worked just fine, even on the
recently updated “Freestyle Libre 3+”. After
the sixty minute calibration period, I had a continuous readout in Juggluco.

CGM‘s lower latency
feedback enables diabetics to have more control of their illness
management. one example among many: the patient can see (in real time)
what foods most often cause blood sugar spikes for
them personally. Diabetes hits everyone differently; data allows
everyone to manage their own chronic condition better.

My personal story with Juggluco will continue — as I hope (although
not until after FOSDEM 2026 😆) to become an upstream contributor to
Juggluco. Most importantly, I hope to help the app appear in F-Droid. (I
must currently side-load or use Aurora Store to make it work on
LineageOS.)

Fitting with the history that many projects that interact with proprietary
technology must so often live through, Juggluco has
faced surreptitious
removal from Google’s Play Store. Abbott even accused Juggluco of
using their proprietary libraries and encryption methods, but the so-called
“encryption method” is literally sending an single integer as
part of NFC activation.

While Abbott backed off, this is another example of why the movement of
patients taking control of the technology remains
essential. FOSS
fits perfectly with this goal. Software freedom gives control of
technology to those who actually rely on it — rather than for-profit
medical equipment manufacturers.

When I returned to my specialist for a follow-up, we reviewed the data and
graphs that I produced with Juggluco. I, of course, have never installed,
used, or even agreed to Abbott’s licenses and terms, so I have never seen
what the Abbott app does. I was thus surprised when I showed my specialist
Juggluco’s summary graphs. He excitedly told me “this is much better
reporting than the Abbott app gives you!”. We all know that
sometimes proprietary software has better and more features than the FOSS
equivalent, so it’s a particularly great success when our community efforts
outdoes a wealthy 200 billion-dollar megacorp on software features!

Please do watch SFC’s site in 2026 for more posts about my ongoing work
with Juggluco, and
please give generously as an
SFC Sustainer to help this and our other work continue in 2026!

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/11/06/juggluco-foss-continuous-glucose-montior-diabetes.html

[ The below is a cross-post of an article that I published on my blog
at Software Freedom Conservancy. ]

Our member project representatives and others who collaborate with
SFC on projects
know that I’ve been on part-time medical leave this year. As I recently announced publicly on the Fediverse, I was diagnosed in March 2025 with early-stage Type
2 Diabetes. I had no idea that that the diagnosis would become a
software freedom and users’ rights endeavor.

After the diagnosis, my doctor suggested immediately that I see the diabetes nurse-practitioner
specialist in their practice. It took some time get an appointment with him,
so I saw him first in mid-April 2025.

I walked into the office, sat down, and within minutes the specialist
asked me to “take out your phone and install the Freestyle Libre app
from Abbott”. This is the first (but, will probably not be the only) time a medical practitioner
asked me to install proprietary software as the first step of
treatment.

The specialist told me that in his experience, even early-stage diabetics
like me should use a Continuous Glucose Monitor (CGM). CGM’s
are an amazing (relatively) recent invention that allows diabetics to
sample their blood sugar level constantly. As we software developers and
engineers know: great things happen when your diagnostic readout is as low
latency as possible. CGMs lower the latency of readouts from 3–4
times a day to every five minutes. For example, diabetics can see
what foods are most likely to cause blood sugar spikes for them
personally. CGMs put patients on a path to manage this chronic condition
well.

But, the devices themselves, and the (default) apps that control them are
hopelessly proprietary. Fortunately, this was (obviously) not my first time
explaining
FOSS from first
principles. So, I read through the license and terms and conditions of the
ironically named “Freestyle Libre” app, and pointed out to the
specialist how patient-unfriendly the terms were. For example, Abbott (the
manufacturer of my CGM) reserves the right to collect your data
(anonymously of course, to “improve the product”). They also
require patients to agree that if they take any action to reverse engineer,
modify, or otherwise do the normal things our community does with
software, the patient must agree that such actions “constitute
immediate, irreparable harm to Abbott, its affiliates, and/or its
licensors”. I briefly explained to the specialist that I could not
possibly agree. I began in real-time (still sitting with the specialist) a
search for a FOSS solution.

As I was searching, the specialist said: “Oh, I don’t use any of it
myself, but I think I’ve heard of this ‘open source’ thing
— there is a program called xDrip+ that is for insulin-dependent
diabetics that I’ve heard of and some patients report it is quite
good”.

While I’m (luckily) very far from insulin-dependency, I eventually found
the FOSS Android app called
Juggluco (a
portmanteau for “Juggle glucose”). I asked the specialist to
give me the prescription and I’d try Juggluco to see if it would work.

CGM‘s are very small
and their firmware is (by obvious necessity) quite simple. As such, their
interfaces are standard. CGM’s are activated with Near Field Communication
(NFC) — available on even quite old Android devices.
The Android device sends a simple integer identifier via NFC that activates
the CGM. Once activated — and through the 15-day life of the device
— the device responds via Bluetooth with the patient’s current
glucose reading to any device presenting that integer.

Fortunately, I quickly discovered that the FOSS community was already
“on this”. The NFC activation worked just fine, even on the
recently updated “Freestyle Libre 3+”. After
the sixty minute calibration period, I had a continuous readout in Juggluco.

CGM‘s lower latency
feedback enables diabetics to have more control of their illness
management. one example among many: the patient can see (in real time)
what foods most often cause blood sugar spikes for
them personally. Diabetes hits everyone differently; data allows
everyone to manage their own chronic condition better.

My personal story with Juggluco will continue — as I hope (although
not until after FOSDEM 2026 😆) to become an upstream contributor to
Juggluco. Most importantly, I hope to help the app appear in F-Droid. (I
must currently side-load or use Aurora Store to make it work on
LineageOS.)

Fitting with the history that many projects that interact with proprietary
technology must so often live through, Juggluco has
faced surreptitious
removal from Google’s Play Store. Abbott even accused Juggluco of
using their proprietary libraries and encryption methods, but the so-called
“encryption method” is literally sending an single integer as
part of NFC activation.

While Abbott backed off, this is another example of why the movement of
patients taking control of the technology remains
essential. FOSS
fits perfectly with this goal. Software freedom gives control of
technology to those who actually rely on it — rather than for-profit
medical equipment manufacturers.

When I returned to my specialist for a follow-up, we reviewed the data and
graphs that I produced with Juggluco. I, of course, have never installed,
used, or even agreed to Abbott’s licenses and terms, so I have never seen
what the Abbott app does. I was thus surprised when I showed my specialist
Juggluco’s summary graphs. He excitedly told me “this is much better
reporting than the Abbott app gives you!”. We all know that
sometimes proprietary software has better and more features than the FOSS
equivalent, so it’s a particularly great success when our community efforts
outdoes a wealthy 200 billion-dollar megacorp on software features!

Please do watch SFC’s site in 2026 for more posts about my ongoing work
with Juggluco, and
please give generously as an
SFC Sustainer to help this and our other work continue in 2026!

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/09/02/ai-llm-hallucination-ballyhoo.html

Big Tech seeks every advantage to convince users that computing is
revolutionized by the latest fad. When the tipping point of Large
Language Models (LLMs) was reached a few years ago,
generative Artificial Intelligence (AI) systems quickly
became that latest snake oil for sale on the carnival podium.

There’s so much to criticize about generative AI, but I focus now merely on the
pseudo-scientific rhetoric adopted to describe the LLM-backed
user-interactive systems in common use today. “Ugh, what a
convoluted phrase”, you may ask, “why not call them
‘chat bots’ like everyone else?” Because “chat
bot” exemplifies the very anthropomorphic hyperbole of
concern.

Too often, software freedom activists (including me — 😬) have asked us to
police our language as an advocacy tactic. Herein, I seek not to cajole everyone
to end AI anthropomorphism. I suggest rather that, when you
write about the latest Big Tech craze, ask yourself: Is my
rhetoric actually reinforcing the message of the very bad actors that I
seek to criticize?

This work now has interested parities with varied motivations. Researchers, for example,
will usually
admit that
they have nothing to contribute to philosophical debates about whether it is
appropriate to … [anthropomorphize] … machines. But
researchers also can never resist a nascent area of study — so all
the academic disclaimers do not prevent the “world of
tomorrow” exuberance
expressed
by those whose work is now the flavor of the month (especially after they toiled at it for
decades in relative obscurity). Computer science (CS)
academics are too closely tied to the Big Tech gravy train even in mundane
times. But when the VCs
stand on their disruptor soap-boxes and make it rain 💸? … Some corners of CS
academia do become a capitalist echo chamber.

The research behind these LLM-backed generative AI systems is (mostly) not
actually new. There’s just more electricity, CPUs/GPUs, & digital data available now. When given
ungodly resources, well-known techniques began yielding novel results. That allowed for quicker incremental (not exponential) improvement. But, a revolution it is not.

I once asked a fellow CS graduate student (in the mid-1990s), who was
presenting their neural net — built with DoD funding to spot tanks behind
trees —, the simple question⁰: Do you know why it’s wrong when
it’s wrong and why it’s right when it’s right?. She grimaced and
answered: Not at all. It doesn’t think.. 30 years later, machines still don’t think.

Precisely there lies the danger of anthropomorphization. While we may never
know why our fellow humans believe what they believe —
after centuries that brought¹ Heraclitus, Aristotle, Aquinas, Bacon,
Decartes, Kant, Kierkegaard, and Haack — we do know that people think, and therefore,
they are. Computers aren’t.
Software isn’t. When we who are succumb to the capitalist chicanery
and erroneously project being unto these systems, we take our first step toward
relinquishing our inherent power over these systems.

Counter-intuitively, the most dangerous are the AI anthropomorphism that criticize rather
than laud the systems. The worst of these, “hallucination”, is
insidious. Appropriation of a
diagnostic term from the DSM-5 into CS literature is abhorrent — prima facie . The term
leads the reader to the Bizarro world where programmers are doctors who
heal sick programs for the betterment of society. Annoyingly and
ironically — even if we did wish to anthropomorphize — LLM-backed generative AI systems almost never
hallucinate. If one were to insist on lifting an analogous term from mental illness diagnosis
(which I obviously don’t recommend), the term is “delusional”.
Frankly, having spent hundreds of hours of my life talking with a mentally
ill family member who is frequently delusional but has almost never
hallucinated — and having to learn to delineate the two for the
purpose of assisting in the individual’s care — I find it downright
offensive and triggering that either term could possibly be used to
describe a thing rather than a person.

Sadly, Big Tech really wants us to jump (not walk) to the conclusion that these systems
are human — or, at least, as beloved pets that we can’t
imagine living without. Critics like me are easily framed as Luddites
when we’ve been socially manipulated into viewing — as “almost
human” — these machines poised to replace the artisans, the law enforcers, and the grocery stockers. Like many of you, I read
Asimov as a child. I later cheered during ST:TNG S02E09 (“Measure of a
Man”) when Lawyer Picard established Mr. Data’s right to sentience
by shouting:
Your Honour, Starfleet was founded to seek out new life. Well, there it
sits. But, I assure you as someone who has devoted much of my life to
considering the moral and ethical implication of Big Tech: they have
yet to give us Mr. Data — and if they eventually do, that Mr. Data²
is
probably going to work for ICE, not Starfleet. Remember, Noonien Soong’s
fictional positronic opus was altruistic only because Soong worked in a post-scarcity society.

While I was still working on a draft of this
essay, Eryk
Salvaggio’s essay “Human Literacy” was published.
Salvaggio makes excellent further reading on the points above.

🎶

Footnotes:

⁰I always find that, in science, the answers simplest questions are always
the most illuminating. I’m reminded how Clifford Stoll wrote about the
most pertinent question at his PhD Physics prelims was “why is the
sky blue?”.

¹I
really just picked a list of my favorite epistemologists here that sounded
good when stated in a row; I apologize in advance if I left out your
favorite from the list.

²I realize fellow
Star Trek fans will say I was moving my lips and nothing came out but a
bunch of gibberish because I forgot about Lore. 😛 I didn’t forget about
Lore; that, my readers, would have to be a topic for a different blog
post.

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/09/02/ai-llm-hallucination-ballyhoo.html

Big Tech seeks every advantage to convince users that computing is
revolutionized by the latest fad. When the tipping point of Large
Language Models (LLMs) was reached a few years ago,
generative Artificial Intelligence (AI) systems quickly
became that latest snake oil for sale on the carnival podium.

There’s so much to criticize about generative AI, but I focus now merely on the
pseudo-scientific rhetoric adopted to describe the LLM-backed
user-interactive systems in common use today. “Ugh, what a
convoluted phrase”, you may ask, “why not call them
‘chat bots’ like everyone else?” Because “chat
bot” exemplifies the very anthropomorphic hyperbole of
concern.

Too often, software freedom activists (including me — 😬) have asked us to
police our language as an advocacy tactic. Herein, I seek not to cajole everyone
to end AI anthropomorphism. I suggest rather that, when you
write about the latest Big Tech craze, ask yourself: Is my
rhetoric actually reinforcing the message of the very bad actors that I
seek to criticize?

This work now has interested parities with varied motivations. Researchers, for example,
will usually
admit that
they have nothing to contribute to philosophical debates about whether it is
appropriate to … [anthropomorphize] … machines. But
researchers also can never resist a nascent area of study — so all
the academic disclaimers do not prevent the “world of
tomorrow” exuberance
expressed
by those whose work is now the flavor of the month (especially after they toiled at it for
decades in relative obscurity). Computer science (CS)
academics are too closely tied to the Big Tech gravy train even in mundane
times. But when the VCs
stand on their disruptor soap-boxes and make it rain 💸? … Some corners of CS
academia do become a capitalist echo chamber.

The research behind these LLM-backed generative AI systems is (mostly) not
actually new. There’s just more electricity, CPUs/GPUs, & digital data available now. When given
ungodly resources, well-known techniques began yielding novel results. That allowed for quicker incremental (not exponential) improvement. But, a revolution it is not.

I once asked a fellow CS graduate student (in the mid-1990s), who was
presenting their neural net — built with DoD funding to spot tanks behind
trees —, the simple question⁰: Do you know why it’s wrong when
it’s wrong and why it’s right when it’s right?. She grimaced and
answered: Not at all. It doesn’t think.. 30 years later, machines still don’t think.

Precisely there lies the danger of anthropomorphization. While we may never
know why our fellow humans believe what they believe —
after centuries that brought¹ Heraclitus, Aristotle, Aquinas, Bacon,
Decartes, Kant, Kierkegaard, and Haack — we do know that people think, and therefore,
they are. Computers aren’t.
Software isn’t. When we who are succumb to the capitalist chicanery
and erroneously project being unto these systems, we take our first step toward
relinquishing our inherent power over these systems.

Counter-intuitively, the most dangerous are the AI anthropomorphism that criticize rather
than laud the systems. The worst of these, “hallucination”, is
insidious. Appropriation of a
diagnostic term from the DSM-5 into CS literature is abhorrent — prima facie . The term
leads the reader to the Bizarro world where programmers are doctors who
heal sick programs for the betterment of society. Annoyingly and
ironically — even if we did wish to anthropomorphize — LLM-backed generative AI systems almost never
hallucinate. If one were to insist on lifting an analogous term from mental illness diagnosis
(which I obviously don’t recommend), the term is “delusional”.
Frankly, having spent hundreds of hours of my life talking with a mentally
ill family member who is frequently delusional but has almost never
hallucinated — and having to learn to delineate the two for the
purpose of assisting in the individual’s care — I find it downright
offensive and triggering that either term could possibly be used to
describe a thing rather than a person.

Sadly, Big Tech really wants us to jump (not walk) to the conclusion that these systems
are human — or, at least, as beloved pets that we can’t
imagine living without. Critics like me are easily framed as Luddites
when we’ve been socially manipulated into viewing — as “almost
human” — these machines poised to replace the artisans, the law enforcers, and the grocery stockers. Like many of you, I read
Asimov as a child. I later cheered during ST:TNG S02E09 (“Measure of a
Man”) when Lawyer Picard established Mr. Data’s right to sentience
by shouting:
Your Honour, Starfleet was founded to seek out new life. Well, there it
sits. But, I assure you as someone who has devoted much of my life to
considering the moral and ethical implication of Big Tech: they have
yet to give us Mr. Data — and if they eventually do, that Mr. Data²
is
probably going to work for ICE, not Starfleet. Remember, Noonien Soong’s
fictional positronic opus was altruistic only because Soong worked in a post-scarcity society.

While I was still working on a draft of this
essay, Eryk
Salvaggio’s essay “Human Literacy” was published.
Salvaggio makes excellent further reading on the points above.

Footnotes:

⁰I always find that, in science, the answers simplest questions are always
the most illuminating. I’m reminded how Clifford Stoll wrote about the
most pertinent question at his PhD Physics prelims was “why is the
sky blue?”.

¹I
really just picked a list of my favorite epistemologists here that sounded
good when stated in a row; I apologize in advance if I left out your
favorite from the list.

²I realize fellow
Star Trek fans will say I was moving my lips and nothing came out but a
bunch of gibberish because I forgot about Lore. 😛 I didn’t forget about
Lore; that, my readers, would have to be a topic for a different blog
post.

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/09/02/ai-llm-hallucination-ballyhoo.html

Big Tech seeks every advantage to convince users that computing is
revolutionized by the latest fad. When the tipping point of Large
Language Models (LLMs) was reached a few years ago,
generative Artificial Intelligence (AI) systems quickly
became that latest snake oil for sale on the carnival podium.

There’s so much to criticize about generative AI, but I focus now merely on the
pseudo-scientific rhetoric adopted to describe the LLM-backed
user-interactive systems in common use today. “Ugh, what a
convoluted phrase”, you may ask, “why not call them
‘chat bots’ like everyone else?” Because “chat
bot” exemplifies the very anthropomorphic hyperbole of
concern.

Too often, software freedom activists (including me — 😬) have asked us to
police our language as an advocacy tactic. Herein, I seek not to cajole everyone
to end AI anthropomorphism. I suggest rather that, when you
write about the latest Big Tech craze, ask yourself: Is my
rhetoric actually reinforcing the message of the very bad actors that I
seek to criticize?

This work now has interested parities with varied motivations. Researchers, for example,
will usually
admit that
they have nothing to contribute to philosophical debates about whether it is
appropriate to … [anthropomorphize] … machines. But
researchers also can never resist a nascent area of study — so all
the academic disclaimers do not prevent the “world of
tomorrow” exuberance
expressed
by those whose work is now the flavor of the month (especially after they toiled at it for
decades in relative obscurity). Computer science (CS)
academics are too closely tied to the Big Tech gravy train even in mundane
times. But when the VCs
stand on their disruptor soap-boxes and make it rain 💸? … Some corners of CS
academia do become a capitalist echo chamber.

The research behind these LLM-backed generative AI systems is (mostly) not
actually new. There’s just more electricity, CPUs/GPUs, & digital data available now. When given
ungodly resources, well-known techniques began yielding novel results. That allowed for quicker incremental (not exponential) improvement. But, a revolution it is not.

I once asked a fellow CS graduate student (in the mid-1990s), who was
presenting their neural net — built with DoD funding to spot tanks behind
trees —, the simple question⁰: Do you know why it’s wrong when
it’s wrong and why it’s right when it’s right?. She grimaced and
answered: Not at all. It doesn’t think.. 30 years later, machines still don’t think.

Precisely there lies the danger of anthropomorphization. While we may never
know why our fellow humans believe what they believe —
after centuries that brought¹ Heraclitus, Aristotle, Aquinas, Bacon,
Decartes, Kant, Kierkegaard, and Haack — we do know that people think, and therefore,
they are. Computers aren’t.
Software isn’t. When we who are succumb to the capitalist chicanery
and erroneously project being unto these systems, we take our first step toward
relinquishing our inherent power over these systems.

Counter-intuitively, the most dangerous are the AI anthropomorphism that criticize rather
than laud the systems. The worst of these, “hallucination”, is
insidious. Appropriation of a
diagnostic term from the DSM-5 into CS literature is abhorrent — prima facie . The term
leads the reader to the Bizarro world where programmers are doctors who
heal sick programs for the betterment of society. Annoyingly and
ironically — even if we did wish to anthropomorphize — LLM-backed generative AI systems almost never
hallucinate. If one were to insist on lifting an analogous term from mental illness diagnosis
(which I obviously don’t recommend), the term is “delusional”.
Frankly, having spent hundreds of hours of my life talking with a mentally
ill family member who is frequently delusional but has almost never
hallucinated — and having to learn to delineate the two for the
purpose of assisting in the individual’s care — I find it downright
offensive and triggering that either term could possibly be used to
describe a thing rather than a person.

Sadly, Big Tech really wants us to jump (not walk) to the conclusion that these systems
are human — or, at least, as beloved pets that we can’t
imagine living without. Critics like me are easily framed as Luddites
when we’ve been socially manipulated into viewing — as “almost
human” — these machines poised to replace the artisans, the law enforcers, and the grocery stockers. Like many of you, I read
Asimov as a child. I later cheered during ST:TNG S02E09 (“Measure of a
Man”) when Lawyer Picard established Mr. Data’s right to sentience
by shouting:
Your Honour, Starfleet was founded to seek out new life. Well, there it
sits. But, I assure you as someone who has devoted much of my life to
considering the moral and ethical implication of Big Tech: they have
yet to give us Mr. Data — and if they eventually do, that Mr. Data²
is
probably going to work for ICE, not Starfleet. Remember, Noonien Soong’s
fictional positronic opus was altruistic only because Soong worked in a post-scarcity society.

While I was still working on a draft of this
essay, Eryk
Salvaggio’s essay “Human Literacy” was published.
Salvaggio makes excellent further reading on the points above.

🎶

Footnotes:

⁰I always find that, in science, the answers simplest questions are always
the most illuminating. I’m reminded how Clifford Stoll wrote about the
most pertinent question at his PhD Physics prelims was “why is the
sky blue?”.

¹I
really just picked a list of my favorite epistemologists here that sounded
good when stated in a row; I apologize in advance if I left out your
favorite from the list.

²I realize fellow
Star Trek fans will say I was moving my lips and nothing came out but a
bunch of gibberish because I forgot about Lore. 😛 I didn’t forget about
Lore; that, my readers, would have to be a topic for a different blog
post.

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/09/02/ai-llm-hallucination-ballyhoo.html

Big Tech seeks every advantage to convince users that computing is
revolutionized by the latest fad. When the tipping point of Large
Language Models (LLMs) was reached a few years ago,
generative Artificial Intelligence (AI) systems quickly
became that latest snake oil for sale on the carnival podium.

There’s so much to criticize about generative AI, but I focus now merely on the
pseudo-scientific rhetoric adopted to describe the LLM-backed
user-interactive systems in common use today. “Ugh, what a
convoluted phrase”, you may ask, “why not call them
‘chat bots’ like everyone else?” Because “chat
bot” exemplifies the very anthropomorphic hyperbole of
concern.

Too often, software freedom activists (including me — 😬) have asked us to
police our language as an advocacy tactic. Herein, I seek not to cajole everyone
to end AI anthropomorphism. I suggest rather that, when you
write about the latest Big Tech craze, ask yourself: Is my
rhetoric actually reinforcing the message of the very bad actors that I
seek to criticize?

This work now has interested parities with varied motivations. Researchers, for example,
will usually
admit that
they have nothing to contribute to philosophical debates about whether it is
appropriate to … [anthropomorphize] … machines. But
researchers also can never resist a nascent area of study — so all
the academic disclaimers do not prevent the “world of
tomorrow” exuberance
expressed
by those whose work is now the flavor of the month (especially after they toiled at it for
decades in relative obscurity). Computer science (CS)
academics are too closely tied to the Big Tech gravy train even in mundane
times. But when the VCs
stand on their disruptor soap-boxes and make it rain 💸? … Some corners of CS
academia do become a capitalist echo chamber.

The research behind these LLM-backed generative AI systems is (mostly) not
actually new. There’s just more electricity, CPUs/GPUs, & digital data available now. When given
ungodly resources, well-known techniques began yielding novel results. That allowed for quicker incremental (not exponential) improvement. But, a revolution it is not.

I once asked a fellow CS graduate student (in the mid-1990s), who was
presenting their neural net — built with DoD funding to spot tanks behind
trees —, the simple question⁰: Do you know why it’s wrong when
it’s wrong and why it’s right when it’s right?. She grimaced and
answered: Not at all. It doesn’t think.. 30 years later, machines still don’t think.

Precisely there lies the danger of anthropomorphization. While we may never
know why our fellow humans believe what they believe —
after centuries that brought¹ Heraclitus, Aristotle, Aquinas, Bacon,
Decartes, Kant, Kierkegaard, and Haack — we do know that people think, and therefore,
they are. Computers aren’t.
Software isn’t. When we who are succumb to the capitalist chicanery
and erroneously project being unto these systems, we take our first step toward
relinquishing our inherent power over these systems.

Counter-intuitively, the most dangerous are the AI anthropomorphism that criticize rather
than laud the systems. The worst of these, “hallucination”, is
insidious. Appropriation of a
diagnostic term from the DSM-5 into CS literature is abhorrent — prima facie . The term
leads the reader to the Bizarro world where programmers are doctors who
heal sick programs for the betterment of society. Annoyingly and
ironically — even if we did wish to anthropomorphize — LLM-backed generative AI systems almost never
hallucinate. If one were to insist on lifting an analogous term from mental illness diagnosis
(which I obviously don’t recommend), the term is “delusional”.
Frankly, having spent hundreds of hours of my life talking with a mentally
ill family member who is frequently delusional but has almost never
hallucinated — and having to learn to delineate the two for the
purpose of assisting in the individual’s care — I find it downright
offensive and triggering that either term could possibly be used to
describe a thing rather than a person.

Sadly, Big Tech really wants us to jump (not walk) to the conclusion that these systems
are human — or, at least, as beloved pets that we can’t
imagine living without. Critics like me are easily framed as Luddites
when we’ve been socially manipulated into viewing — as “almost
human” — these machines poised to replace the artisans, the law enforcers, and the grocery stockers. Like many of you, I read
Asimov as a child. I later cheered during ST:TNG S02E09 (“Measure of a
Man”) when Lawyer Picard established Mr. Data’s right to sentience
by shouting:
Your Honour, Starfleet was founded to seek out new life. Well, there it
sits. But, I assure you as someone who has devoted much of my life to
considering the moral and ethical implication of Big Tech: they have
yet to give us Mr. Data — and if they eventually do, that Mr. Data²
is
probably going to work for ICE, not Starfleet. Remember, Noonien Soong’s
fictional positronic opus was altruistic only because Soong worked in a post-scarcity society.

While I was still working on a draft of this
essay, Eryk
Salvaggio’s essay “Human Literacy” was published.
Salvaggio makes excellent further reading on the points above.

Footnotes:

⁰I always find that, in science, the answers simplest questions are always
the most illuminating. I’m reminded how Clifford Stoll wrote about the
most pertinent question at his PhD Physics prelims was “why is the
sky blue?”.

¹I
really just picked a list of my favorite epistemologists here that sounded
good when stated in a row; I apologize in advance if I left out your
favorite from the list.

²I realize fellow
Star Trek fans will say I was moving my lips and nothing came out but a
bunch of gibberish because I forgot about Lore. 😛 I didn’t forget about
Lore; that, my readers, would have to be a topic for a different blog
post.

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/09/02/ai-llm-hallucination-ballyhoo.html

Big Tech seeks every advantage to convince users that computing is
revolutionized by the latest fad. When the tipping point of Large
Language Models (LLMs) was reached a few years ago,
generative Artificial Intelligence (AI) systems quickly
became that latest snake oil for sale on the carnival podium.

There’s so much to criticize about generative AI, but I focus now merely on the
pseudo-scientific rhetoric adopted to describe the LLM-backed
user-interactive systems in common use today. “Ugh, what a
convoluted phrase”, you may ask, “why not call them
‘chat bots’ like everyone else?” Because “chat
bot” exemplifies the very anthropomorphic hyperbole of
concern.

Too often, software freedom activists (including me — 😬) have asked us to
police our language as an advocacy tactic. Herein, I seek not to cajole everyone
to end AI anthropomorphism. I suggest rather that, when you
write about the latest Big Tech craze, ask yourself: Is my
rhetoric actually reinforcing the message of the very bad actors that I
seek to criticize?

This work now has interested parities with varied motivations. Researchers, for example,
will usually
admit that
they have nothing to contribute to philosophical debates about whether it is
appropriate to … [anthropomorphize] … machines. But
researchers also can never resist a nascent area of study — so all
the academic disclaimers do not prevent the “world of
tomorrow” exuberance
expressed
by those whose work is now the flavor of the month (especially after they toiled at it for
decades in relative obscurity). Computer science (CS)
academics are too closely tied to the Big Tech gravy train even in mundane
times. But when the VCs
stand on their disruptor soap-boxes and make it rain 💸? … Some corners of CS
academia do become a capitalist echo chamber.

The research behind these LLM-backed generative AI systems is (mostly) not
actually new. There’s just more electricity, CPUs/GPUs, & digital data available now. When given
ungodly resources, well-known techniques began yielding novel results. That allowed for quicker incremental (not exponential) improvement. But, a revolution it is not.

I once asked a fellow CS graduate student (in the mid-1990s), who was
presenting their neural net — built with DoD funding to spot tanks behind
trees —, the simple question⁰: Do you know why it’s wrong when
it’s wrong and why it’s right when it’s right?. She grimaced and
answered: Not at all. It doesn’t think.. 30 years later, machines still don’t think.

Precisely there lies the danger of anthropomorphization. While we may never
know why our fellow humans believe what they believe —
after centuries that brought¹ Heraclitus, Aristotle, Aquinas, Bacon,
Decartes, Kant, Kierkegaard, and Haack — we do know that people think, and therefore,
they are. Computers aren’t.
Software isn’t. When we who are succumb to the capitalist chicanery
and erroneously project being unto these systems, we take our first step toward
relinquishing our inherent power over these systems.

Counter-intuitively, the most dangerous are the AI anthropomorphism that criticize rather
than laud the systems. The worst of these, “hallucination”, is
insidious. Appropriation of a
diagnostic term from the DSM-5 into CS literature is abhorrent — prima facie . The term
leads the reader to the Bizarro world where programmers are doctors who
heal sick programs for the betterment of society. Annoyingly and
ironically — even if we did wish to anthropomorphize — LLM-backed generative AI systems almost never
hallucinate. If one were to insist on lifting an analogous term from mental illness diagnosis
(which I obviously don’t recommend), the term is “delusional”.
Frankly, having spent hundreds of hours of my life talking with a mentally
ill family member who is frequently delusional but has almost never
hallucinated — and having to learn to delineate the two for the
purpose of assisting in the individual’s care — I find it downright
offensive and triggering that either term could possibly be used to
describe a thing rather than a person.

Sadly, Big Tech really wants us to jump (not walk) to the conclusion that these systems
are human — or, at least, as beloved pets that we can’t
imagine living without. Critics like me are easily framed as Luddites
when we’ve been socially manipulated into viewing — as “almost
human” — these machines poised to replace the artisans, the law enforcers, and the grocery stockers. Like many of you, I read
Asimov as a child. I later cheered during ST:TNG S02E09 (“Measure of a
Man”) when Lawyer Picard established Mr. Data’s right to sentience
by shouting:
Your Honour, Starfleet was founded to seek out new life. Well, there it
sits. But, I assure you as someone who has devoted much of my life to
considering the moral and ethical implication of Big Tech: they have
yet to give us Mr. Data — and if they eventually do, that Mr. Data²
is
probably going to work for ICE, not Starfleet. Remember, Noonien Soong’s
fictional positronic opus was altruistic only because Soong worked in a post-scarcity society.

While I was still working on a draft of this
essay, Eryk
Salvaggio’s essay “Human Literacy” was published.
Salvaggio makes excellent further reading on the points above.

Footnotes:

⁰I always find that, in science, the answers simplest questions are always
the most illuminating. I’m reminded how Clifford Stoll wrote about the
most pertinent question at his PhD Physics prelims was “why is the
sky blue?”.

¹I
really just picked a list of my favorite epistemologists here that sounded
good when stated in a row; I apologize in advance if I left out your
favorite from the list.

²I realize fellow
Star Trek fans will say I was moving my lips and nothing came out but a
bunch of gibberish because I forgot about Lore. 😛 I didn’t forget about
Lore; that, my readers, would have to be a topic for a different blog
post.

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/09/02/ai-llm-hallucination-ballyhoo.html

Big Tech seeks every advantage to convince users that computing is
revolutionized by the latest fad. When the tipping point of Large
Language Models (LLMs) was reached a few years ago,
generative Artificial Intelligence (AI) systems quickly
became that latest snake oil for sale on the carnival podium.

There’s so much to criticize about generative AI, but I focus now merely on the
pseudo-scientific rhetoric adopted to describe the LLM-backed
user-interactive systems in common use today. “Ugh, what a
convoluted phrase”, you may ask, “why not call them
‘chat bots’ like everyone else?” Because “chat
bot” exemplifies the very anthropomorphic hyperbole of
concern.

Too often, software freedom activists (including me — 😬) have asked us to
police our language as an advocacy tactic. Herein, I seek not to cajole everyone
to end AI anthropomorphism. I suggest rather that, when you
write about the latest Big Tech craze, ask yourself: Is my
rhetoric actually reinforcing the message of the very bad actors that I
seek to criticize?

This work now has interested parities with varied motivations. Researchers, for example,
will usually
admit that
they have nothing to contribute to philosophical debates about whether it is
appropriate to … [anthropomorphize] … machines. But
researchers also can never resist a nascent area of study — so all
the academic disclaimers do not prevent the “world of
tomorrow” exuberance
expressed
by those whose work is now the flavor of the month (especially after they toiled at it for
decades in relative obscurity). Computer science (CS)
academics are too closely tied to the Big Tech gravy train even in mundane
times. But when the VCs
stand on their disruptor soap-boxes and make it rain 💸? … Some corners of CS
academia do become a capitalist echo chamber.

The research behind these LLM-backed generative AI systems is (mostly) not
actually new. There’s just more electricity, CPUs/GPUs, & digital data available now. When given
ungodly resources, well-known techniques began yielding novel results. That allowed for quicker incremental (not exponential) improvement. But, a revolution it is not.

I once asked a fellow CS graduate student (in the mid-1990s), who was
presenting their neural net — built with DoD funding to spot tanks behind
trees —, the simple question⁰: Do you know why it’s wrong when
it’s wrong and why it’s right when it’s right?. She grimaced and
answered: Not at all. It doesn’t think.. 30 years later, machines still don’t think.

Precisely there lies the danger of anthropomorphization. While we may never
know why our fellow humans believe what they believe —
after centuries that brought¹ Heraclitus, Aristotle, Aquinas, Bacon,
Decartes, Kant, Kierkegaard, and Haack — we do know that people think, and therefore,
they are. Computers aren’t.
Software isn’t. When we who are succumb to the capitalist chicanery
and erroneously project being unto these systems, we take our first step toward
relinquishing our inherent power over these systems.

Counter-intuitively, the most dangerous are the AI anthropomorphism that criticize rather
than laud the systems. The worst of these, “hallucination”, is
insidious. Appropriation of a
diagnostic term from the DSM-5 into CS literature is abhorrent — prima facie . The term
leads the reader to the Bizarro world where programmers are doctors who
heal sick programs for the betterment of society. Annoyingly and
ironically — even if we did wish to anthropomorphize — LLM-backed generative AI systems almost never
hallucinate. If one were to insist on lifting an analogous term from mental illness diagnosis
(which I obviously don’t recommend), the term is “delusional”.
Frankly, having spent hundreds of hours of my life talking with a mentally
ill family member who is frequently delusional but has almost never
hallucinated — and having to learn to delineate the two for the
purpose of assisting in the individual’s care — I find it downright
offensive and triggering that either term could possibly be used to
describe a thing rather than a person.

Sadly, Big Tech really wants us to jump (not walk) to the conclusion that these systems
are human — or, at least, as beloved pets that we can’t
imagine living without. Critics like me are easily framed as Luddites
when we’ve been socially manipulated into viewing — as “almost
human” — these machines poised to replace the artisans, the law enforcers, and the grocery stockers. Like many of you, I read
Asimov as a child. I later cheered during ST:TNG S02E09 (“Measure of a
Man”) when Lawyer Picard established Mr. Data’s right to sentience
by shouting:
Your Honour, Starfleet was founded to seek out new life. Well, there it
sits. But, I assure you as someone who has devoted much of my life to
considering the moral and ethical implication of Big Tech: they have
yet to give us Mr. Data — and if they eventually do, that Mr. Data²
is
probably going to work for ICE, not Starfleet. Remember, Noonien Soong’s
fictional positronic opus was altruistic only because Soong worked in a post-scarcity society.

While I was still working on a draft of this
essay, Eryk
Salvaggio’s essay “Human Literacy” was published.
Salvaggio makes excellent further reading on the points above.

🎶

Footnotes:

⁰I always find that, in science, the answers simplest questions are always
the most illuminating. I’m reminded how Clifford Stoll wrote about the
most pertinent question at his PhD Physics prelims was “why is the
sky blue?”.

¹I
really just picked a list of my favorite epistemologists here that sounded
good when stated in a row; I apologize in advance if I left out your
favorite from the list.

²I realize fellow
Star Trek fans will say I was moving my lips and nothing came out but a
bunch of gibberish because I forgot about Lore. 😛 I didn’t forget about
Lore; that, my readers, would have to be a topic for a different blog
post.

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/09/02/ai-llm-hallucination-ballyhoo.html

Big Tech seeks every advantage to convince users that computing is
revolutionized by the latest fad. When the tipping point of Large
Language Models (LLMs) was reached a few years ago,
generative Artificial Intelligence (AI) systems quickly
became that latest snake oil for sale on the carnival podium.

There’s so much to criticize about generative AI, but I focus now merely on the
pseudo-scientific rhetoric adopted to describe the LLM-backed
user-interactive systems in common use today. “Ugh, what a
convoluted phrase”, you may ask, “why not call them
‘chat bots’ like everyone else?” Because “chat
bot” exemplifies the very anthropomorphic hyperbole of
concern.

Too often, software freedom activists (including me — 😬) have asked us to
police our language as an advocacy tactic. Herein, I seek not to cajole everyone
to end AI anthropomorphism. I suggest rather that, when you
write about the latest Big Tech craze, ask yourself: Is my
rhetoric actually reinforcing the message of the very bad actors that I
seek to criticize?

This work now has interested parities with varied motivations. Researchers, for example,
will usually
admit that
they have nothing to contribute to philosophical debates about whether it is
appropriate to … [anthropomorphize] … machines. But
researchers also can never resist a nascent area of study — so all
the academic disclaimers do not prevent the “world of
tomorrow” exuberance
expressed
by those whose work is now the flavor of the month (especially after they toiled at it for
decades in relative obscurity). Computer science (CS)
academics are too closely tied to the Big Tech gravy train even in mundane
times. But when the VCs
stand on their disruptor soap-boxes and make it rain 💸? … Some corners of CS
academia do become a capitalist echo chamber.

The research behind these LLM-backed generative AI systems is (mostly) not
actually new. There’s just more electricity, CPUs/GPUs, & digital data available now. When given
ungodly resources, well-known techniques began yielding novel results. That allowed for quicker incremental (not exponential) improvement. But, a revolution it is not.

I once asked a fellow CS graduate student (in the mid-1990s), who was
presenting their neural net — built with DoD funding to spot tanks behind
trees —, the simple question⁰: Do you know why it’s wrong when
it’s wrong and why it’s right when it’s right?. She grimaced and
answered: Not at all. It doesn’t think.. 30 years later, machines still don’t think.

Precisely there lies the danger of anthropomorphization. While we may never
know why our fellow humans believe what they believe —
after centuries that brought¹ Heraclitus, Aristotle, Aquinas, Bacon,
Decartes, Kant, Kierkegaard, and Haack — we do know that people think, and therefore,
they are. Computers aren’t.
Software isn’t. When we who are succumb to the capitalist chicanery
and erroneously project being unto these systems, we take our first step toward
relinquishing our inherent power over these systems.

Counter-intuitively, the most dangerous are the AI anthropomorphism that criticize rather
than laud the systems. The worst of these, “hallucination”, is
insidious. Appropriation of a
diagnostic term from the DSM-5 into CS literature is abhorrent — prima facie . The term
leads the reader to the Bizarro world where programmers are doctors who
heal sick programs for the betterment of society. Annoyingly and
ironically — even if we did wish to anthropomorphize — LLM-backed generative AI systems almost never
hallucinate. If one were to insist on lifting an analogous term from mental illness diagnosis
(which I obviously don’t recommend), the term is “delusional”.
Frankly, having spent hundreds of hours of my life talking with a mentally
ill family member who is frequently delusional but has almost never
hallucinated — and having to learn to delineate the two for the
purpose of assisting in the individual’s care — I find it downright
offensive and triggering that either term could possibly be used to
describe a thing rather than a person.

Sadly, Big Tech really wants us to jump (not walk) to the conclusion that these systems
are human — or, at least, as beloved pets that we can’t
imagine living without. Critics like me are easily framed as Luddites
when we’ve been socially manipulated into viewing — as “almost
human” — these machines poised to replace the artisans, the law enforcers, and the grocery stockers. Like many of you, I read
Asimov as a child. I later cheered during ST:TNG S02E09 (“Measure of a
Man”) when Lawyer Picard established Mr. Data’s right to sentience
by shouting:
Your Honour, Starfleet was founded to seek out new life. Well, there it
sits. But, I assure you as someone who has devoted much of my life to
considering the moral and ethical implication of Big Tech: they have
yet to give us Mr. Data — and if they eventually do, that Mr. Data²
is
probably going to work for ICE, not Starfleet. Remember, Noonien Soong’s
fictional positronic opus was altruistic only because Soong worked in a post-scarcity society.

While I was still working on a draft of this
essay, Eryk
Salvaggio’s essay “Human Literacy” was published.
Salvaggio makes excellent further reading on the points above.

🎶

Footnotes:

⁰I always find that, in science, the answers simplest questions are always
the most illuminating. I’m reminded how Clifford Stoll wrote about the
most pertinent question at his PhD Physics prelims was “why is the
sky blue?”.

¹I
really just picked a list of my favorite epistemologists here that sounded
good when stated in a row; I apologize in advance if I left out your
favorite from the list.

²I realize fellow
Star Trek fans will say I was moving my lips and nothing came out but a
bunch of gibberish because I forgot about Lore. 😛 I didn’t forget about
Lore; that, my readers, would have to be a topic for a different blog
post.

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/09/02/ai-llm-hallucination-ballyhoo.html

Big Tech seeks every advantage to convince users that computing is
revolutionized by the latest fad. When the tipping point of Large
Language Models (LLMs) was reached a few years ago,
generative Artificial Intelligence (AI) systems quickly
became that latest snake oil for sale on the carnival podium.

There’s so much to criticize about generative AI, but I focus now merely on the
pseudo-scientific rhetoric adopted to describe the LLM-backed
user-interactive systems in common use today. “Ugh, what a
convoluted phrase”, you may ask, “why not call them
‘chat bots’ like everyone else?” Because “chat
bot” exemplifies the very anthropomorphic hyperbole of
concern.

Too often, software freedom activists (including me — 😬) have asked us to
police our language as an advocacy tactic. Herein, I seek not to cajole everyone
to end AI anthropomorphism. I suggest rather that, when you
write about the latest Big Tech craze, ask yourself: Is my
rhetoric actually reinforcing the message of the very bad actors that I
seek to criticize?

This work now has interested parities with varied motivations. Researchers, for example,
will usually
admit that
they have nothing to contribute to philosophical debates about whether it is
appropriate to … [anthropomorphize] … machines. But
researchers also can never resist a nascent area of study — so all
the academic disclaimers do not prevent the “world of
tomorrow” exuberance
expressed
by those whose work is now the flavor of the month (especially after they toiled at it for
decades in relative obscurity). Computer science (CS)
academics are too closely tied to the Big Tech gravy train even in mundane
times. But when the VCs
stand on their disruptor soap-boxes and make it rain 💸? … Some corners of CS
academia do become a capitalist echo chamber.

The research behind these LLM-backed generative AI systems is (mostly) not
actually new. There’s just more electricity, CPUs/GPUs, & digital data available now. When given
ungodly resources, well-known techniques began yielding novel results. That allowed for quicker incremental (not exponential) improvement. But, a revolution it is not.

I once asked a fellow CS graduate student (in the mid-1990s), who was
presenting their neural net — built with DoD funding to spot tanks behind
trees —, the simple question⁰: Do you know why it’s wrong when
it’s wrong and why it’s right when it’s right?. She grimaced and
answered: Not at all. It doesn’t think.. 30 years later, machines still don’t think.

Precisely there lies the danger of anthropomorphization. While we may never
know why our fellow humans believe what they believe —
after centuries that brought¹ Heraclitus, Aristotle, Aquinas, Bacon,
Decartes, Kant, Kierkegaard, and Haack — we do know that people think, and therefore,
they are. Computers aren’t.
Software isn’t. When we who are succumb to the capitalist chicanery
and erroneously project being unto these systems, we take our first step toward
relinquishing our inherent power over these systems.

Counter-intuitively, the most dangerous are the AI anthropomorphism that criticize rather
than laud the systems. The worst of these, “hallucination”, is
insidious. Appropriation of a
diagnostic term from the DSM-5 into CS literature is abhorrent — prima facie . The term
leads the reader to the Bizarro world where programmers are doctors who
heal sick programs for the betterment of society. Annoyingly and
ironically — even if we did wish to anthropomorphize — LLM-backed generative AI systems almost never
hallucinate. If one were to insist on lifting an analogous term from mental illness diagnosis
(which I obviously don’t recommend), the term is “delusional”.
Frankly, having spent hundreds of hours of my life talking with a mentally
ill family member who is frequently delusional but has almost never
hallucinated — and having to learn to delineate the two for the
purpose of assisting in the individual’s care — I find it downright
offensive and triggering that either term could possibly be used to
describe a thing rather than a person.

Sadly, Big Tech really wants us to jump (not walk) to the conclusion that these systems
are human — or, at least, as beloved pets that we can’t
imagine living without. Critics like me are easily framed as Luddites
when we’ve been socially manipulated into viewing — as “almost
human” — these machines poised to replace the artisans, the law enforcers, and the grocery stockers. Like many of you, I read
Asimov as a child. I later cheered during ST:TNG S02E09 (“Measure of a
Man”) when Lawyer Picard established Mr. Data’s right to sentience
by shouting:
Your Honour, Starfleet was founded to seek out new life. Well, there it
sits. But, I assure you as someone who has devoted much of my life to
considering the moral and ethical implication of Big Tech: they have
yet to give us Mr. Data — and if they eventually do, that Mr. Data²
is
probably going to work for ICE, not Starfleet. Remember, Noonien Soong’s
fictional positronic opus was altruistic only because Soong worked in a post-scarcity society.

While I was still working on a draft of this
essay, Eryk
Salvaggio’s essay “Human Literacy” was published.
Salvaggio makes excellent further reading on the points above.

🎶

Footnotes:

⁰I always find that, in science, the answers simplest questions are always
the most illuminating. I’m reminded how Clifford Stoll wrote about the
most pertinent question at his PhD Physics prelims was “why is the
sky blue?”.

¹I
really just picked a list of my favorite epistemologists here that sounded
good when stated in a row; I apologize in advance if I left out your
favorite from the list.

²I realize fellow
Star Trek fans will say I was moving my lips and nothing came out but a
bunch of gibberish because I forgot about Lore. 😛 I didn’t forget about
Lore; that, my readers, would have to be a topic for a different blog
post.

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/09/02/ai-llm-hallucination-ballyhoo.html

Big Tech seeks every advantage to convince users that computing is
revolutionized by the latest fad. When the tipping point of Large
Language Models (LLMs) was reached a few years ago,
generative Artificial Intelligence (AI) systems quickly
became that latest snake oil for sale on the carnival podium.

There’s so much to criticize about generative AI, but I focus now merely on the
pseudo-scientific rhetoric adopted to describe the LLM-backed
user-interactive systems in common use today. “Ugh, what a
convoluted phrase”, you may ask, “why not call them
‘chat bots’ like everyone else?” Because “chat
bot” exemplifies the very anthropomorphic hyperbole of
concern.

Too often, software freedom activists (including me — 😬) have asked us to
police our language as an advocacy tactic. Herein, I seek not to cajole everyone
to end AI anthropomorphism. I suggest rather that, when you
write about the latest Big Tech craze, ask yourself: Is my
rhetoric actually reinforcing the message of the very bad actors that I
seek to criticize?

This work now has interested parities with varied motivations. Researchers, for example,
will usually
admit that
they have nothing to contribute to philosophical debates about whether it is
appropriate to … [anthropomorphize] … machines. But
researchers also can never resist a nascent area of study — so all
the academic disclaimers do not prevent the “world of
tomorrow” exuberance
expressed
by those whose work is now the flavor of the month (especially after they toiled at it for
decades in relative obscurity). Computer science (CS)
academics are too closely tied to the Big Tech gravy train even in mundane
times. But when the VCs
stand on their disruptor soap-boxes and make it rain 💸? … Some corners of CS
academia do become a capitalist echo chamber.

The research behind these LLM-backed generative AI systems is (mostly) not
actually new. There’s just more electricity, CPUs/GPUs, & digital data available now. When given
ungodly resources, well-known techniques began yielding novel results. That allowed for quicker incremental (not exponential) improvement. But, a revolution it is not.

I once asked a fellow CS graduate student (in the mid-1990s), who was
presenting their neural net — built with DoD funding to spot tanks behind
trees —, the simple question⁰: Do you know why it’s wrong when
it’s wrong and why it’s right when it’s right?. She grimaced and
answered: Not at all. It doesn’t think.. 30 years later, machines still don’t think.

Precisely there lies the danger of anthropomorphization. While we may never
know why our fellow humans believe what they believe —
after centuries that brought¹ Heraclitus, Aristotle, Aquinas, Bacon,
Decartes, Kant, Kierkegaard, and Haack — we do know that people think, and therefore,
they are. Computers aren’t.
Software isn’t. When we who are succumb to the capitalist chicanery
and erroneously project being unto these systems, we take our first step toward
relinquishing our inherent power over these systems.

Counter-intuitively, the most dangerous are the AI anthropomorphism that criticize rather
than laud the systems. The worst of these, “hallucination”, is
insidious. Appropriation of a
diagnostic term from the DSM-5 into CS literature is abhorrent — prima facie . The term
leads the reader to the Bizarro world where programmers are doctors who
heal sick programs for the betterment of society. Annoyingly and
ironically — even if we did wish to anthropomorphize — LLM-backed generative AI systems almost never
hallucinate. If one were to insist on lifting an analogous term from mental illness diagnosis
(which I obviously don’t recommend), the term is “delusional”.
Frankly, having spent hundreds of hours of my life talking with a mentally
ill family member who is frequently delusional but has almost never
hallucinated — and having to learn to delineate the two for the
purpose of assisting in the individual’s care — I find it downright
offensive and triggering that either term could possibly be used to
describe a thing rather than a person.

Sadly, Big Tech really wants us to jump (not walk) to the conclusion that these systems
are human — or, at least, as beloved pets that we can’t
imagine living without. Critics like me are easily framed as Luddites
when we’ve been socially manipulated into viewing — as “almost
human” — these machines poised to replace the artisans, the law enforcers, and the grocery stockers. Like many of you, I read
Asimov as a child. I later cheered during ST:TNG S02E09 (“Measure of a
Man”) when Lawyer Picard established Mr. Data’s right to sentience
by shouting:
Your Honour, Starfleet was founded to seek out new life. Well, there it
sits. But, I assure you as someone who has devoted much of my life to
considering the moral and ethical implication of Big Tech: they have
yet to give us Mr. Data — and if they eventually do, that Mr. Data²
is
probably going to work for ICE, not Starfleet. Remember, Noonien Soong’s
fictional positronic opus was altruistic only because Soong worked in a post-scarcity society.

While I was still working on a draft of this
essay, Eryk
Salvaggio’s essay “Human Literacy” was published.
Salvaggio makes excellent further reading on the points above.

🎶

Footnotes:

⁰I always find that, in science, the answers simplest questions are always
the most illuminating. I’m reminded how Clifford Stoll wrote about the
most pertinent question at his PhD Physics prelims was “why is the
sky blue?”.

¹I
really just picked a list of my favorite epistemologists here that sounded
good when stated in a row; I apologize in advance if I left out your
favorite from the list.

²I realize fellow
Star Trek fans will say I was moving my lips and nothing came out but a
bunch of gibberish because I forgot about Lore. 😛 I didn’t forget about
Lore; that, my readers, would have to be a topic for a different blog
post.

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/09/02/ai-llm-hallucination-ballyhoo.html

Big Tech seeks every advantage to convince users that computing is
revolutionized by the latest fad. When the tipping point of Large
Language Models (LLMs) was reached a few years ago,
generative Artificial Intelligence (AI) systems quickly
became that latest snake oil for sale on the carnival podium.

There’s so much to criticize about generative AI, but I focus now merely on the
pseudo-scientific rhetoric adopted to describe the LLM-backed
user-interactive systems in common use today. “Ugh, what a
convoluted phrase”, you may ask, “why not call them
‘chat bots’ like everyone else?” Because “chat
bot” exemplifies the very anthropomorphic hyperbole of
concern.

Too often, software freedom activists (including me — 😬) have asked us to
police our language as an advocacy tactic. Herein, I seek not to cajole everyone
to end AI anthropomorphism. I suggest rather that, when you
write about the latest Big Tech craze, ask yourself: Is my
rhetoric actually reinforcing the message of the very bad actors that I
seek to criticize?

This work now has interested parities with varied motivations. Researchers, for example,
will usually
admit that
they have nothing to contribute to philosophical debates about whether it is
appropriate to … [anthropomorphize] … machines. But
researchers also can never resist a nascent area of study — so all
the academic disclaimers do not prevent the “world of
tomorrow” exuberance
expressed
by those whose work is now the flavor of the month (especially after they toiled at it for
decades in relative obscurity). Computer science (CS)
academics are too closely tied to the Big Tech gravy train even in mundane
times. But when the VCs
stand on their disruptor soap-boxes and make it rain 💸? … Some corners of CS
academia do become a capitalist echo chamber.

The research behind these LLM-backed generative AI systems is (mostly) not
actually new. There’s just more electricity, CPUs/GPUs, & digital data available now. When given
ungodly resources, well-known techniques began yielding novel results. That allowed for quicker incremental (not exponential) improvement. But, a revolution it is not.

I once asked a fellow CS graduate student (in the mid-1990s), who was
presenting their neural net — built with DoD funding to spot tanks behind
trees —, the simple question⁰: Do you know why it’s wrong when
it’s wrong and why it’s right when it’s right?. She grimaced and
answered: Not at all. It doesn’t think.. 30 years later, machines still don’t think.

Precisely there lies the danger of anthropomorphization. While we may never
know why our fellow humans believe what they believe —
after centuries that brought¹ Heraclitus, Aristotle, Aquinas, Bacon,
Decartes, Kant, Kierkegaard, and Haack — we do know that people think, and therefore,
they are. Computers aren’t.
Software isn’t. When we who are succumb to the capitalist chicanery
and erroneously project being unto these systems, we take our first step toward
relinquishing our inherent power over these systems.

Counter-intuitively, the most dangerous are the AI anthropomorphism that criticize rather
than laud the systems. The worst of these, “hallucination”, is
insidious. Appropriation of a
diagnostic term from the DSM-5 into CS literature is abhorrent — prima facie . The term
leads the reader to the Bizarro world where programmers are doctors who
heal sick programs for the betterment of society. Annoyingly and
ironically — even if we did wish to anthropomorphize — LLM-backed generative AI systems almost never
hallucinate. If one were to insist on lifting an analogous term from mental illness diagnosis
(which I obviously don’t recommend), the term is “delusional”.
Frankly, having spent hundreds of hours of my life talking with a mentally
ill family member who is frequently delusional but has almost never
hallucinated — and having to learn to delineate the two for the
purpose of assisting in the individual’s care — I find it downright
offensive and triggering that either term could possibly be used to
describe a thing rather than a person.

Sadly, Big Tech really wants us to jump (not walk) to the conclusion that these systems
are human — or, at least, as beloved pets that we can’t
imagine living without. Critics like me are easily framed as Luddites
when we’ve been socially manipulated into viewing — as “almost
human” — these machines poised to replace the artisans, the law enforcers, and the grocery stockers. Like many of you, I read
Asimov as a child. I later cheered during ST:TNG S02E09 (“Measure of a
Man”) when Lawyer Picard established Mr. Data’s right to sentience
by shouting:
Your Honour, Starfleet was founded to seek out new life. Well, there it
sits. But, I assure you as someone who has devoted much of my life to
considering the moral and ethical implication of Big Tech: they have
yet to give us Mr. Data — and if they eventually do, that Mr. Data²
is
probably going to work for ICE, not Starfleet. Remember, Noonien Soong’s
fictional positronic opus was altruistic only because Soong worked in a post-scarcity society.

While I was still working on a draft of this
essay, Eryk
Salvaggio’s essay “Human Literacy” was published.
Salvaggio makes excellent further reading on the points above.

🎶

Footnotes:

⁰I always find that, in science, the answers simplest questions are always
the most illuminating. I’m reminded how Clifford Stoll wrote about the
most pertinent question at his PhD Physics prelims was “why is the
sky blue?”.

¹I
really just picked a list of my favorite epistemologists here that sounded
good when stated in a row; I apologize in advance if I left out your
favorite from the list.

²I realize fellow
Star Trek fans will say I was moving my lips and nothing came out but a
bunch of gibberish because I forgot about Lore. 😛 I didn’t forget about
Lore; that, my readers, would have to be a topic for a different blog
post.

Post Syndicated from Bradley M. Kuhn original http://ebb.org/bkuhn/blog/2025/07/06/copyleft-next-relaunch.html

I am excited that Richard Fontana and I
have announced
the relaunch of copyleft-next.

The copyleft-next project seeks to
create a copyleft license for the next generation that is designed in
public, by the community, using standard processes for FOSS
development.

If this interests you,
please join the
mailing list and follow the
project on the fediverse (on its Mastodon instance).

I also wanted to note that as part of this launch, I moved my personal
fediverse presence from
floss.social to [email protected].