The impact of increasingly powerful electronics on our society cannot be overstated. These more powerful electronics produce significant heat that must be dissipated to prevent premature component failure. Engineers that design electronics face a significant thermal management challenge. Electrical engineers frequently seek to increase the power of critical components, and keeping these components cool represents a significant design challenge. This design task becomes even more challenging when the cooling systems rely on natural convection instead of forced convection from fans, due to the relatively short life expectancy of fans.
One solution to this engineering challenge is to use multiphysics software tools to improve the accuracy of the engineer’s calculations in comparison to analytic and single-physics simulation solutions. These simulations include heat generated by the component, airflow around the component, and radiative heat transfer between the component and the surroundings. Heat generation due to resistive heating in the board can be included with heat generated from components to determine the heat generated within the system. Airflow through the system due to either forced or natural convection can also be analyzed. For many systems, radiation must be considered for accurate temperature predictions due to the large amount of heat transfer that occurs via this mechanism in many electronic designs.
In this presentation, guest speakers Kyle Koppenhoefer and Joshua Thomas from AltaSim Technologies will discuss the development of an electronics cooling problem subjected to a complex thermal environment. The webinar will also include a live demo in the COMSOL Multiphysics® software and a Q&A session.
This is a guest post. The views expressed here are those of the authors and do not necessarily represent positions of IEEE or its organizational units.
Robotics is a fast-growing field with important economic and societal impacts. Despite the relevance of robotics, however, there is little diversity among educators and researchers in the area. This problem is especially acute among Black scholars and is not improving. In this article, we outline the representation problem and introduce a reading list along with suggestions for how those in academia—researchers, teachers, students, conference organizers, and others—can take actions that increase Black representation in robotics. While our analysis focuses on the situation in the United States, we hope that our suggestions will be of use to colleagues in other countries as well.
In 2019, the typical tech professional IEEE member earned US $148,500 in 2019, excluding overtime, profit sharing, and side hustles. That’s up from $145,000 in 2018, a 2.4 percent increase, leaving real income virtually unchanged. It’s also a smaller bump than the 4.5 percent increase that 2018saw over 2017.
That’s the topline news in the 2020 edition of the IEEE-USA Salary & Benefits Survey, released this month. But other numbers paint a more nuanced picture.
In spite of the salaries staying relatively flat, job satisfaction is way up. The survey used a scale of -2 to +2 to calculate average satisfaction in several categories. Overall satisfaction broke the 1.0 mark for the first time in 2019. The jump affected all categories of satisfaction tracked in recent years, including engineers’ satisfaction with technical challenges, employer’s support for technical vitality, compensation, and opportunities for advancement.
The survey added several new questions to the satisfaction category in 2019, including whether a respondent’s work is meaningful (1.14), respected (1.13), and offers a work-life balance (0.73). It will be interesting to see how those numbers trend next year, when the survey will reflect the impact of the pandemic.
Engineers in Consumer Electronics Rise to the Top
Tech professionals working in consumer electronics claimed the highest median income in 2019 according to IEEE-USA’s numbers, at $185,000. (This year’s survey did not breakout a median for smartphone developers, who topped the charts in 2018, because there were too few responses.) Educators, with a median income of $105,707, fell to the bottom of the list. And, somewhat surprising to me, the median salary of respondents working in machine learning dropped from $185,000 in 2018 to $130,800 in 2019.
Gender Salary Gap Continues to Grow
Data from tech professionals identifying as female who responded to the survey was certainly less comprehensive than those identifying as male—only 8.6 percent of respondents working full time in their primary area of technical concept identified were in that group. Still, the numbers reported were troubling. The overall difference between male and females in median income in 2019 was $22,500, 18 percent more than the $19,000 gap in 2018. (A recent study by job search firm Hired discovered a widening gap as well, while a study by Dice found that, while the gap persists, some differences by specialty are emerging.)
Racial Disparities in Income Grow Too
And the gap between Caucasians and African-Americans grew as well, from $20,500 in 2018 to $22,000 in 2019. Again, the number of respondents was small. (A Hired study found a $10,000 gap.)
Pacific Region’s Dominance Increases
The geographic gap between income reported by respondents to IEEE-USA’s annual salary survey is growing. The Pacific Region’s 2019 $171,000 median income rose nearly $2300 over 2018. But salaries in New England, the region that has consistently reported the second highest median income, stayed flat at $150,000.
California came out on top again in the state rankings, at $180,684, an increase of slightly less than $1000 from 2018.
IEEE-USA’s Salary & Benefits Survey 2020, conducted online, received 8209 responses, an 8.7 percent response rate. After excluding those working outside their primary area of technical competence, full-time students, retirees, and other outliers, 5993 responses were tallied for most of question sets. The vast majority of the respondents were non-Hispanic white men, with a median age of 50. The full 63-page report is available from the IEEE-USA’s salary service.
Planning of satellite communication links or even whole networks is a very demanding task. In the first part of this webinar, we will present our software for satellite link planning that supports the user in a convenient way but takes into the account all relevant sources of impact. In the second part of the webinar, we will demonstrate our solution for monitoring satellite networks, either at one site or distributed worldwide. In addition, we will put focus on the identification of interference coming from unwanted satellite signals or terrestrial sources. We will also show how to make interfering signals that lie underneath the wanted satellite carrier visible.
Attendees of the webinar will learn about:
• The sources of impact affecting satellite links
• How to plan satellite links or whole satellite networks
• The best way to monitor your satellite connections automated and reliably
Six years ago, Jeremy Johnson, visited Nairobi to speak at an education summit. Fresh off of taking his startup, 2U, public he saw a lot of smart young people—but not a lot of opportunity. With his background building 2U, he thought that was a problem he could do at least a little something about.
Along with five other entrepreneurs, Johnson started Andela. The company’s mission: to use digital education tools to train software engineers, and then place those engineers in jobs they could perform remotely for companies around the world.
The response from would-be software engineers—initially in Lagos, then expanding to six countries in Africa and recently announcing a continent-wide push—was overwhelming.
“We did a pilot in Lagos in 2014,” Johnson recalled, “by putting out a call for applicants… We were looking to select four people; we had 750 apply and hired six.”
Andela put the group through six months of training before placing them in jobs with tech companies from outside Africa.
For the second pilot program, with 20 slots to fill, Andela brought in an independent testing service to conduct aptitude tests to whittle down the pool of 2400 applicants. “The testing service called us, and asked us if we were aware that 42 applicants tested in the top two percent for cognitive ability of anybody in the world.”
Johnson and his partners realized that they had identified a population of really smart people who wanted to be software engineers. Initially, they aimed to provide free job training for the inexperienced. Then, once they were trained, hire them to work on projects that Andela took on for companies around the world. After five years and training more than 100,000 aspiring engineers in Africa, Andela realized that access to job training was no longer the prime hurdle for aspiring engineers, and dropped the training part of its operation to focus on bringing jobs to already experienced software engineers.
Right now, Andela has more than 1000 developers on its staff, spread throughout six countries in Africa and working for several hundred companies, with 2019 revenues of around $50 million. It’s not a nonprofit—the individuals and firms who have invested $181 million to date expect a financial return.
Navigating the pandemic in the short run has been challenging, says Johnson, though in the long run the sudden and massive switch of tech employers to remote work is likely to be a boon to engineers in Africa.
Here’s what else Johnson has to say about Andela’s operation, the impact of the coronavirus, and prospects for the future.
How Andela manages its remote workforce:
“We generally bring someone on for a specific job for a specific company; they are paid through Andela. Basically, we make global hiring local [by handling all the logistics].
“To set salaries, we look at local markets. We try to be on the generous side of fair in regards to local market, so we can attract the best talent. However, we don’t want to break local markets; we don’t want people leaving medical and legal professions to become software developers. That said, the average engineer coming in gets a 30 percent pay bump from their previous role.
[Companies generally contract with Andela for a fixed number of engineers for a fixed amount of time. But Andela tries to keep its staff on board.]
“Once we know someone is going to be rolling off, we start looking for their next job.”
On the impact of the pandemic:
“This has not been a simple year. We saw the storm start to build in February, across the board. We got really worried in March, because we had so many small business clients. And indeed, in March and April, we saw a significant slowdown in new relationships, in companies being able to make hiring decisions.
[In May, Andela cut 135 employees, mostly operations and back office; no engineers were affected. Senior management also took a pay cut.]
“But we maintained more than 90 percent of our relationships with companies; things there went much better than expected. And in June, saw a turnaround on both sides, with things becoming much smoother.”
On the future of remote work:
“The pandemic and move to remote work increases the obviousness of what we are doing. We are going to see over time a significant shift to building out remote teams as a default strategy, a portion or the entire strategy, accelerating a trend that has been developing for years.
“We are seeing a move to grow the remote workforce in new customers and existing companies. We have also seen a lot of our partner companies who haven’t announced permanent remote work, tell us that they don’t have a timeline for bringing people back into the office, and remote work may be permanent.
“Long term, this is going to be a significant tailwind; it puts everyone on a level playing field. Businesses start working with us because [of the cost savings compared with hiring local talent]. And that’s fine. But from our point of view, we also want to leave the world better than we found it. That happens when a CTO wakes up six months after they start working with us, and realizes that the best engineer on the team is a young woman from Nairobi. It’s fun getting that ‘I love your mission’ call and knowing that this just happened.”
On Africa’s brain drain:
“If you want to keep people you need to create opportunities for them. It’s not complex. I think of us as being a driver of enabling people to stay in country and build a local ecosystem—to have a local ecosystem you need opportunities that allow people to stay. Giving engineers an opportunity to work with the best engineering teams in the world, while staying in their country, allows them to bring knowledge home; that also contributes to building their own ecosystem, and ultimately creating even more opportunity there.”
The Tower of Pisa is indeed a famous monument. Yet, it is also a monumental error of civil engineering. Built in 1173 with no foundations on a flood plain, the white marble tower started tipping on its southern side even before it was completed. Its peculiar inclination is like a spectacular warning to all builders around the world.
Yet, people have studied the ground under their feet, way before the 12th century. They have done so ever since they started extracting rock, building houses and bridges and digging irrigation systems. At first purely empirical, soil investigation has been rationalised since the 17th century and has given rise to geotechnics, a technoscience combining geology and geomechanics.
Today, the most frequently used measurement instrument in geotechnics is the penetrometer. “Imagine it as a giant hydraulic press that digs a measurement cone in the ground…” explains Paolo Bruzzi, Pagani Geotechnical’s sales manager. The Italian company, whose factory is based in Piacenza, near Milan, has become a global leader in the field of geotechnical equipment.
Penetrometers render high-fidelity images: “Our equipment detects layers – sand, clay or other – as thin as 10-15 cm.” Enough to make reliable estimates on soil behaviour when building a road or a bridge, digging foundations or simply setting up the pillar of a ski lift.
As for all measurement instruments, the quality of penetrometers depends on their reliability. “The system verifies itself its accuracy after every measurement”, explains Paolo Bruzzi. “Incoherent data would immediately signal that the cone had been damaged. So, we can be sure that our measurements are always absolutely precise.” Furthermore, the cones require mandatory calibration every year, a further warranty of correct measurement. Material and processes are standardised defacto on an international level. The cone sizes, the forces applied, the penetration speed … everything is defined to enable traceability, repeatability and data sharing.
Penetrometer tests can be used for other types of measurements as well. In particular, for seismic measurements. “In such cases, we stop penetrating after every meter and create a seismic wave from the surface” explains Bruzzi. “Its amplitude and propagation speed is measured by a sensor on the cone, which makes it possible to evaluate the soil’s behaviour in case of earthquakes.”
Anecdotally, the “elastic” soil, isolating the structure from earthquakes, which provoked the tipping of the Tower of Pisa, also protected it from several earthquakes.
The instant results obtained by the penetrometers have greatly contributed to the popularity of these instruments. Carried out in situ, the tests do not require any soil sampling, nor waiting for laboratory analysis results. “They disturb the soil much less than core drilling, so they are less likely to influence the results,” says Paolo Bruzzi.
Whether disturbed or not, ground is not easy to deal with. The equipment must possess huge power to drive in a cone. “In the past, the only solution was using heavy duty trucks, up to 20 tons” recalls Bruzzi. “Such trucks are still used in certain cases and they usually cost in excess of 400,000 euros, require a heavy vehicle driver, an entire team and, since the measurements need to be carried out vertically, a flat, large enough piece of land …”
In a nutshell, a costly and constraining solution. The idea of developing an alternative is how the story of Pagani Geotechnical began.
It all started back in the seventies in Italy. As building requirements were being strengthened, Ermanno Pagani created his geotechnical consulting company. Tests became widely used and the entrepreneur realised that engineers were increasingly using heavy trucks for projects that were much smaller than building bridges or blocks of flats, such as family homes. He wanted to carry out tests with equipment that would be much less disproportionate. Wouldn’t it be possible to have a penetrometer capable of analysing with precision the first 20-25m of soil (deep enough for a large number of projects), but that would be more compact, easy to use and much less costly than geotechnical trucks? Since he couldn’t find anything to meet such needs, he developed his own equipment. As it attracted his customers’ attention, he could foresee the potential market and launched his business. Since then, Pagani Geotechnical stopped being a consultant, and became a manufacturer. His first penetrometers were sold in 1983.
A year later, the company launched its TG 73-200 model, a modular and mobile device. Its mast can be tilted forward and backward enabling measurement even on sloping terrain. It anchors automatically into the ground so that it can exert the necessary thrust, in spite of its modest 3 tons. Handling, anchoring and measurements are automated to such an extent that only a single operator is needed to carry out the tests.
Pagani has put a particular accent on the robustness of the product. “The TG 73-200 was built to be indestructible” laughs Bruzzi. “It withstands all types of “abuse” – very difficult terrain or heavy-handed, clumsy operators!”
Thanks to these “over the top” characteristics, the 73-200 remained Pagani’s high-end model, selling five of them a year. “Its customers are large companies that require no-compromise performance for some highly demanding applications.” As for other applications, Pagani Geotechnical has taken another step forward.
The TG 63-150, even easier to use, was launched in 1989. It is slightly bigger than 1m by 2m and weighs only a ton. The engineer can transport it himself in a van (no longer a need for a truck and a truck driver) and carry out the measurement on his own. It is a first in its field which simplified the tests and cut the costs considerably. The price (44,000 euros, which is half the price of a 73-200 and close to one tenth of a truck) contributes to broadening the client base – medium-sized companies, consultancy firms, universities, laboratories…
“The 63-150 was the first of its kind”, says Paolo Bruzzi. “It had immediate success. With 800 units sold in over 70 countries, it has even become the best-selling compact penetrometer in the world.” It is still Pagani’s best-seller, who sell over sixty of them every year.
The TG 30-20 and 63-100 completed Pagani’s range of penetrometers. The Italian company, still managed by its founder, employs 25 people. Its factory produces between 70 and 80 machines a year and its 800 customers come from almost 90 countries.
Apart from the engines and hydraulic systems, everything is developed and produced “in-house”: accessories, electronic cones, seismic modules, power units… Even its data acquisition systems, including the new CPT AS, launched this spring, fully fitted with LEMO connectors. “This watertight system needs to operate on all terrain, from snow-covered northern countries to the Amazonian rainforest” explains Bruzzi. “We have chosen IP65 certified LEMO connectors for their resistance and compactness, as well as for aesthetic reasons – the excellence of our solutions also derives from design!”
Pagani’s material is robust (its penetrometers are used for “an average of more than 20 years”). Technical components remain stable (“there hasn’t been found anything better for exploring the soil!”). Improvements are made essentially in the electronics system and the accessories. Two or three annual upgrades optimise measurement precision and ease of use. Safety is reinforced to follow the continuous evolution of regulations. Applications have become mobile.
“Many innovations arise from our partnerships with universities and research centres in Italy, Brazil, England or other countries, and, obviously, from feedback from our 800 customers from almost 90 countries, who use our technologies regularly in all possible conditions: in jungles, frozen soil, deserts …”
Pagani, proudly claiming “Made in Italy”, is happy to be associated with high quality. The durability of its machines hasn’t hindered regular sales progress for the last few years. For what reason? There’s been a growing demand for geotechnical tests. “The quality of infrastructures has been improving, requirements have become stricter and additional countries, in particular in emerging economies, have started performing tests.” In short, everything is done to ensure that the Tower of Pisa stays unrivalled.
Learn about automotive design, test and measurement tips anytime, anywhere. Join our experts as they cover the latest topics including: Delivering Quiet Power to Automotive Electronics and Challenges and Solutions of Advanced Automotive Radar System Design. Explore these topics and more at your convenience.
Rocket, a startup that builds AI-based tools for recruiters and offers recruitment services of its own, had been on the verge of profitability whenthe coronavirus pandemic hit. It quickly saw corporate recruitment pushes dry up.
With the pause in hiring affecting its main business and mounting layoffs at tech companies, Rocket turned its efforts towards matching laid off engineers with new jobs pro bono. Rocket gathered data on layoffs, set its AI software andrecruiters on cleaning up the data and making it easier to navigate, and launched a new portal to the data. Dubbed Parachute, the portal now has 13,500 professionals from around the world on its original, U.S.-based English-language site, and Rocket is bringing up sister sites in other countries.
Here’s what Rocket cofounder and CEO Abhinav Agrawal had to say when IEEE Spectrum talked to him this month about the pandemic’s effect on tech jobs, creating Parachute, and what he sees for tech careers on the near horizon.
On the effect of the pandemic on tech jobs:
Abhinav Agrawal: “When Covid hit, we saw companies scaled back hiring almost immediately. As soon as companies started working from home—in early to mid-February—they became cautious in hiring. Interviewing took a big hit; we had all been conditioned to believe that interviewing in person was the gold standard, so a lot of candidates were impacted as interviews were pushed out or cancelled until they could be rescheduled in person.
“Then, as the market demands started softening, you had startups going into self-preservation mode. Prominent venture capitalists issued advisories to their portfolio companies, saying that winter is coming, so it is time to flip from growth at all costs to let’s batten down the hatches and survive this.
“Right now, we are in purgatory. We are seeing about a third of companies going straight ahead with hiring, a third just tiptoeing back in, and about a third sitting in survival mode [and not hiring at all].”
On interviewing in a pandemic:
Agrawal: “The process is completely changing. On-site interviews in four to five hours in a stretch are out the window. That’s been challenging for a lot of senior engineering leaders who like to do whiteboard interviews and are having to adapt.
“We are also finding that not being able to meet someone in person, makes it harder to believe your judgement—to sense fit—so people instead of doing three on site interviews are doing maybe five zoom interviews.”
On the impact of working from home:
Agrawal: “Initially, people still wanted to hire people in their headquarters’ city. But now, with companies doing fine with remote workers, people are wondering if they should look for candidates outside their headquarter cities, that even when office environments come back, they can still hire remote workers. Companies are, however, focused on the candidates in the headquarters’ time zone—looking at, say, Seattle, Los Angeles, and Latin America. Being in the same time zone makes collaboration easier.
“There are [salary] implications. People at every company we talk to are having difficult conversations internally about how to manage that. If current employees want to move, they say, ‘What do we do about salaries? Do we have different bands for different cities? Do we penalize them for moving?’ These are tough conversations companies are now having.”
On layoffs and starting Parachute:
Agrawal: “We saw layoffs starting to happen, even before the lockdowns. First they were in in concentrated industries, like building software for local retail, restaurant operations, and travel. By early April, we could see layoffs were beginning to escalate. Now we are hopefully on the other side of the peak of the curve, but layoffs are still trickling through.Companies that thought they could ride it out are starting to think they can’t, they might have thought [the pandemic] would be a couple of months; well it’s July now, and things could be worse in the Fall.
“Pretty early on we started thinking about how to help the community [of laid off tech professionals] and recruiters. There are a couple of issues in layoffs.
“For one, it’s hard to know exactly who at a company has been laid off when they announce, say that they have laid off 25 percent of their workforce. If you reach out at random, you’ll find three out of four people weren’t laid off.
“Second, there is a stigma around layoffs, so often people won’t mention that they’ve been laid off. But if layoff information is institutionalized, becomes a platform, and top companies are hiring there, it takes the stigma away.
“So we thought it would be great if there were a centralized place where recruiters could access data and reach out directly.
“We get the data from three sources. Sometimes, we work directly with companies doing a layoff to offer an opt-in [to our service]. We did that with the HR team at Lyft.
“We also look at publicly available spreadsheets or lists. These are sometimes set up by a coworker, or someone in HR; the formats vary a lot. We only use these when the information is available publicly. And we remove anybody on those lists who contacts us, we try to do that within an hour of being notified. Finally, you can sign up directly on Parachutelist.com.
“Then we standardize the data, which is challenging. Even something like “Bay Area,” people will say San Francisco, SF, Peninsula. We also try to standardize job functions and titles. Our AI tools take a first pass. They will, for example, ingest what someone does based on a description given, then give [the job] a standardized title, calculate years of experience, and label the region. They also , extract skills from a resume and standardize those to make them searchable. AI gets about 80 to 90 percent of the cases right, but we still have a human review every profile, to look for edge cases.
“We started building Parachute right about when lockdown started. We did a soft launch at end of April, started getting word out in early May. Right now, we have 13,500 on the list from all over the world—we had people signing up in India, Dubai, Chile, New Zealand, Australia, Europe, and Nigeria. We now have a Spanish language version now live in Chile, and we have Israeli and French versions in the works. We are continuing to make improvements in how we ingest data and bring people on.
“We have candidates from just about every tech layoff that happened, like Uber, Lyft, Airbnb, Peerspace, and WeWork. We have several thousand recruiters using it, from every major company, like Facebook, Amazon, Apple, and Twitter on the big side, to Coinbase, Shift, and Doximity on the small side. We’ve had verified recruiters reach out to candidates from our platform 25,000 times; generally, mid-level professionals are getting the most interest. We don’t know how many have been hired; because we aren’t charging anybody for this service we don’t have a good way of tracking them. We have received more than 150 emails from professionals letting us know, but we believe the real number is two to three times that.
“My hope is that the need for this product goes away. It’s a weird thing, you build a product, but you actually aren’t hoping that it gets more use.”
Although quantum computing is still in its infancy, its potential means it has already become one of the fastest-growing STEM fields. Consequently, industry and academia are now starting to tackle the problem of creating a labor pool that can leverage the opportunities provided by this new field.
It’s likely that any future quantum workforce will have to come from a diverse universe of scientists and engineers, including material scientists and electronic engineers working on hardware and code developers and mathematicians working on software.
This was the view of education leaders from IBM, NYU and Howard University at a recent virtual meeting set up to discuss the challenges of the anticipated quantum computing talent shortage.
“You have to have advanced education in order to make a good living in this industry,” explained Tina Brower-Thomas, Education Director and Howard University Executive Director, Center for Integrated Quantum Materials. “So the question is are we preparing our K through 12 to go to the schools that have requisite curriculum that will then prepare them to be in the industry? I think, unfortunately, the answer is “no” and that’s a long-standing problem we’ve had in this country.”
IBM has been trying to pull both industry and academia together to prepare for the day when quantum computing requires a large number of trained professionals. One of IBM’s initiatives has been its Qiskit Global Summer School for future quantum software developers (prerequisites are the ability to multiply two matrices and basic Python programming experience). Qiskit has already had over 5,000 students from around the world apply to it.
Cloud-based systems mean no longer having a “huge barrier to entry where you have to learn quantum mechanics and then you have to learn several other things along the way. You can make the barrier a little bit lower to just a question of programming,” said Asfaw.
While being able to program cloud-based systems has democratized the field somewhat, Javad Shabani, Assistant Professor of Physics and Chair of the Shabani Lab, New York University, believes that if we’re looking for a generation that are really going to make breakthroughs, they’re going have to learn the hardware of quantum computers.
“In quantum computing at this stage in its development, you can’t separate software and hardware,” said Shabani. “We know that we don’t have a perfect quantum computer, so in order to make a little improvement you need to know the quantum computer inside and out [because of] the errors that exist in the quantum computers.”
The experiences of Shabani, Asfaw and Brower-Thomas all confirmed that even if you engage people early, broaden the spectrum of people who come into the field, a key issue is being able to offer students realistic and practical expectations of what they can expect in the immediate future for the themselves.
Shabani noted: “We all like to talk about the great potential of quantum computing, but these great capabilities come with great challenges. So we need to be careful about the hype and explain to students the realities of these great challenges and that they also create great opportunities.”
Two years ago, Amazon reportedly scrapped a secret artificial intelligence hiring tool after realizing that the system had learned to prefer male job candidates while penalizing female applicants—the result of the AI training on resumes that mostly male candidates had submitted to the company. The episode raised concerns over the use of machine learning in hiring software that would perpetuate or even exacerbate existing biases.
Now, with the Black Lives Matter movement spurring new discussions about discrimination and equity issues within the workforce, a number of startups are trying to show that AI-powered recruiting tools can in fact play a positive role in mitigating human bias and help make the hiring process fairer.
These companies claim that, with careful design and training of their AI models, they were able to specifically address various sources of systemic bias in the recruitment pipeline. It’s not a simple task: AI algorithms have a long historyof being unfairregarding gender,race, and ethnicity. The strategies adopted by these companies include scrubbing identifying information from applications, relying on anonymous interviews and skillset tests, and even tuning the wording of job postings to attract as diverse a field of candidates as possible.
One of these firms is GapJumpers, which offers a platform for applicants to take “blind auditions” designed to assess job-related skills. The startup, based in San Francisco, uses machine learning to score and rank each candidate without including any personally identifiable information. Co-founder and CEO Kedar Iyer says this methodology helps reduce traditional reliance on resumes, which as a source of training data is “riddled with bias,” and avoids unwittingly replicating and propagating such biases through the scaled-up reach of automated recruiting.
That deliberate approach to reducing discrimination may be encouraging more companies to try AI-assisted recruiting. As the Black Lives Matter movement gained widespread support, GapJumpers saw an uptick in queries from potential clients. “We are seeing increased interest from companies of all sizes to improve their diversity efforts,” Iyers says.
AI with humans in the loop
Another lesson from Amazon’s gender-biased AI is that paying close attention to the design and training of the system is not enough: AI software will almost always require constant human oversight. For developers and recruiters, that means they cannot afford to blindly trust the results of AI-powered tools—they need to understand the processes behind them, how different training data affects their behavior, and monitor for bias.
“One of the unintended consequences would be to continue this historical trend, particularly in tech, where underserved groups such as African Americans are not within a sector that happens to have a compensation that is much greater than others,” saysFay Cobb Payton, a professor of information technology and analytics at North Carolina State University, in Raleigh. “You’re talking about a wealth gap that persists because groups cannot enter [such sectors], be sustained, and play long term.”
Payton and her colleagues highlighted several companies—including GapJumpers—that take an “intentional design justice” approach to hiring diverse IT talent in a paper published last year in the journal Online Information Review.
According to the paper’s authors, there is a broad spectrum of possible actions that AI hiring tools can perform. Some tools may just provide general suggestions about what kind of candidate to hire, whereas others may recommend specific applicants to human recruiters, and some may even make active screening and selection decisions about candidates. But whatever the AI’s role in the hiring process, there is a need for humans to have the capability to evaluate the system’s decisions and possibly override them.
“I believe that human-in-the-loop should not be at the end of the recommendation that the algorithms suggest,” Payton says. “Human-in-the-loop means in the full process of the loop from design to hire, all the way until the experience inside of the organization.”
Each stage of an AI system’s decision point should allow for an auditing process where humans can check the results, Payton adds. And of course, it’s crucial to have a separation of duties so that the humans auditing the system are not the same as those who designed the system in the first place.
“When we talk about bias, there are so many nuances and spots along this talent acquisition process where bias and bias mitigation come into play,” says Lynette Yarger, a professor of information sciences and technology at Pennsylvania State University and lead author on the paper with Payton. She added that “those companies that are trying to mitigate these biases are interesting because they’re trying to push human beings to be accountable.”
Another example highlighted by Yarger and Payton is a Seattle-based startup called Textio that has trained its AI systems to analyze job advertisements and predict their ability to attract a diverse array of applicants. Textio’s “Tone Meter” can help companies offer job listings with more inclusive language: Phrases like “rock star” that attract more male job seekers could be swapped out for the software’s suggestion of “high performer” instead.
“We use Textio for our own recruiting communication and have from the beginning,” says Kieran Snyder, CEO and co-founder of Textio, which is based in Seattle. “But perhaps because we make the software, we know that Textio on its own is not the whole solution when it comes to building an equitable organization—it’s just one piece of the puzzle.”
Indeed, many tech companies, including those that develop AI-powered hiring tools, are still working on inclusion and equity. Enterprise software company Workday, founded by former PeopleSoft executives and headquartered in Pleasanton, Calif., has more than 3,700 employees worldwide and clients that include half the Fortune 100. During a company forum on diversity and racial bias in June, Workday acknowledged that Black employees make up just 2.4 percent of its U.S. workforce versus the average of 4.4 percent for Silicon Valley firms, according to SearchHRSoftware, a human resources technology news site.
AI hiring tools: not a quick fix
Another challenge for AI-powered recruiting tools is that some customers expect them to offer a quick fix to a complex problem, when in reality that is not the case. James Doman-Pipe, head of product marketing at Headstart, a recruiting software startup based in London, says any business interested in reducing discrimination with AI or other technologies will need significant buy-in from the leadership and other parts of the organization.
Headstart’s software uses machine learning to evaluate job applicants and generate a “match score” that shows how well the candidates fit with a job’s requirements for skills, education, and experience. “By generating a match score, recruiters are more likely to consider underprivileged and underrepresented minorities to move forward in the recruiting process,” Doman-Pipe says. The company claims that in tests comparing the AI-based approach to traditional recruiting methods, clients using its software saw a significant improvements in the diversity makeup of new hires.
Still, one of the greatest obstacles AI-powered recruiting tools face before they can gain widespread trust is the lack of public data showing how different tools can help—or hinder—efforts to making tech hiring more equitable.
“I do know from interviews with software companies that they do audit, and they can go back and recalibrate their systems,” Yarger, the Pennsylvania State University professor, says. But the effectiveness of efforts to improve algorithmic equity in recruitment remain unclear. She explains that many companies remain reluctant to publicly share such information because of liability issues surrounding equitable employment and workplace discrimination. Companies using AI tools could face legal consequences if the tools were shown to discriminate against certain groups groups.
For North Carolina State’s Payton, it remains to be seen whether corporate commitments to addressing diversity and racial bias will have a broader and lasting impact in the hiring and retention of tech workers—and whether or not AI can prove significant in helping to create equitable an workforce.
“Association and confirmation biases and networks that are built into the system, those don’t change overnight,” she says. “So there’s much work to be done.”
Engineering the 5G World provides the information you need to master the complexities of 5G and bring your products to market successfully. Whether you’re designing chipsets, components, devices, or base stations or bringing 5G networks online, we’ve got you covered.
The gap between the average salary offered to black tech professionals and what’s offered to white tech professionals is closing at a snail’s pace. According to an analysis by the job search firm Hired, in 2019 black tech professionals were offered an average of US $10,000 a year less than white tech workers. That’s slightly better than the 2018 gap of $11,000, but not much better.
Meanwhile, Hispanic tech professionals lag $3,000 behind their white counterparts, down from $7,000 in 2019. Asian tech professionals, having pulled ahead in recent years, continue to command a slight edge in average salaries over their white colleagues.
Within each racial group, tech professionals who identified themselves as female received lower average salary offers than their male counterparts, according to Hired’s 2020 State of Wage Inequality in the Workplace Report, released earlier this year.
One promising takeaway from Hired’s 2020 State of Salaries Report was that tech salaries grew in the United States, Canada, and the United Kingdom in 2019, with the U.S. average up to $146,000 (an 8 percent increase over 2018) and the average of all three regions up to $130,000 (a less than 1 percent increase).
Or at least the trend would have been promising, had things not changed so much between the close of 2019 and today. Under normal conditions, the information contained in Hired’s salaries report would be seen as a trend line that would progress into the upcoming year. But what it means right now, in the midst of the coronavirus pandemic, is anyone’s guess.
“Tech headquarters are closed, work from home is the new normal, Amazon and Netflix usage is soaring, well-known tech unicorns like Uber, Lyft, and Airbnb are laying off thousands,” the Hired report states.
Meanwhile, Facebook is looking to adjust salaries up or down based on the cost of living in exchange for the freedom to work remotely. Whether the new normal will ever return to the old normal remains unclear.
Still, it’s worth looking at the gains made in 2019, because we’ll certainly be referring to these numbers as we monitor the engineering jobs marketplace during and after the pandemic.
According to Hired’s analysis, tech workers in Austin and Toronto saw the biggest increase in salary offers, both up 10 percent over 2018.
Still, in terms of raw numbers, average tech salaries in the San Francisco Bay Area remained on top, averaging $155,000 (up 7 percent) in 2019. When salaries are adjusted for the cost of living, though, many regions are well ahead of the San Francisco Bay Area: Austin’s $137,000 annual 2019 salary, for example, is equivalent to a salary of $224,000 in the Bay Area. But recent announcements by large tech companies about adjusting salaries based on the cost of living when their employees relocate may change that picture over the next 12 months.
This article is based on twoposts in our View From the Valley blog.
It’s a new world for businesses everywhere. For small and medium sized companies who thrive on in-person relationships and customer interaction, it’s a difficult transition to an all remote- stay at home workforce. That’s on top of whether your business model can sustain some level of operation, revenue generation, and customer retention.
For those companies who can continue to operate at some level, the current environment creates numerous opportunities for a bad actor to exploit your employees, or for a bad employee to steal from your company. Join us in this webinar to discuss strategies that will help protect your company now by learning the indicators professionals look for in potential problem employees and review the motivations that drive employees to cross the line. You will be equipped with strategies and questions you should ask your leadership to better protect you company in these unprecedented times.
It would be an understatement to say it’s been a turbulent year since the last time IEEE Spectrum broke out the digital measuring tools to probe the relative popularity of programming languages. Yet one thing remains constant: the dominance of Python.
Since it’s impossible for even the most aggressive spy agency in the world to find out what language every single programmer uses when they sit down at their keyboards—especially the ones tapping away on retro computers or even programmable calculators—we rely on combining 11 metrics from online sources that we think are good proxies for the popularity of 55 languages.
Because different programmers have different interests and needs, our online rankings are interactive, allowing you to weight the metrics as you see fit. Think one measure is way more valuable than the others? Max it out. Disagree with us about the worth of another? Turn it off. We have a number of preset rankings that focus on things such as emerging languages or what jobs employers are looking to fill (big thanks to CareerBuilder for making it possible to query their database this year, now that it’s no longer accessible using a public application programming language).
Our default ranking is weighted toward the interests of an IEEE member, and looking at the top entries, we see that Python has held onto its comfortable lead, with Java and C once again coming in second and third place, respectively. Arduino has seen a big jump, rising from 11th place to seventh. (Purists may argue that Arduino is not a language but rather a hardware platform that is programmed using a derivative of Wiring, which itself is derived from C/C++. But we have always taken a very pragmatic approach to our definition of “programming language,” and the reality is that when people are looking to use an Arduino-compatible microcontroller, they typically search for “Arduino code” or buy books about “Arduino programming,” not “Wiring code” or “C programming.”)
One interpretation of Python’s high ranking is that its metrics are inflated by its increasing use as a teaching language: Students are simply asking and searching for the answers to the same elementary questions over and over. There’s an historical parallel here. In the 1980s, BASIC was very visible—there were books, magazines, and even TV programs devoted to the language. But few professional programmers used it, and when the home computer bubble burst, so did BASIC’s, although some advanced descendants like Microsoft Visual Basic are still relatively popular professionally.
There are two counterarguments, though: The first is that students are people, too! If we pay attention only to what professional and expert coders do, we’re at risk of missing an important part of the picture. The second is that, unlike BASIC, Python is frequently used professionally and in high-profile realms, such as machine learning, thanks to its enormous collection of high quality, specialized libraries.
However, the COVID-19 pandemic has left some traces on the 2020 rankings. For example, if you look at the Twitter metric alone in the interactive, you can see that Cobol is in seventh place. This is likely due to the fact that in April, when we were gathering the Twitter data, Cobol was in the news because unemployment benefit systems in U.S. states were crashing under the load as workers were laid off due to lockdowns. It turns out that many of these systems had not been significantly upgraded since they were created decades ago, and a call went out for Cobol programmers to help shore them up.
There’s always a vibrant conversation about Spectrum’s Top Programming Languages online, so we encourage you to explore the full rankings and leave comments there, particularly if you want to nominate an emerging language for inclusion in next year’s rankings.
This article appears in the August 2020 print issue as “The Top Programming Languages.”
Tune into this webinar to learn more about 3D cable modeling. The models can be used to virtually test, design, and optimize cable systems based on accurate multiphysics simulation techniques.
We will demonstrate and discuss best practices to set up models and run simulations. Examples will cover the computation of inductive and thermal cable properties. Topics include:
Geometry creation and meshing
Setting up twisted armor periodicity
Evaluating currents and magnetic losses in the armor
Heating and thermal effects
The live demo in the COMSOL Multiphysics® software will lead you through the typical steps to simulate 3D cables using a high-voltage submarine cable as an example. You can ask questions throughout the webinar or at the end during the Q&A session.
In the wake of new Black Lives Matter protests, one company hopes to use virtual reality to help people better understand others by putting them in their colleagues’ shoes. The aim is to create better workplaces by helping employees develop and practice more respectful ways of interacting with each other.
By immersing people in realistic digital environments, virtual reality (VR) can lead to mind-bending experiences, such as making users feel as if they have swapped bodies with someone else. The effects of VR can persist long after these experiences; psychologists hope this can help in therapies for ailments such as phobias and post-traumatic stress disorder.
In 2014, economist Lisa D. Cook reported research that illuminated something fundamental about innovation: No matter how well your IP laws are written, innovation won’t happen without security and the rule of law. To prove that she showed how segregation laws, lynchings, and state-supported violence suppressed African American invention during the 20th Century. By tracking the patent filings of African American inventors from 1870-1940, Cook showed that acts of violence have a measurable impact on innovation. IEEE Spectrum spoke to the Michigan State University professor of economics and international relations on 2 July 2020.
IEEE Spectrum: What led you to investigate the effects of violence and segregation on African American innovation?
Lisa D. Cook: I wrote my dissertation on Russia and the Russian economy. This was in the 1990s, and it was a bit of a dangerous place. There was a question that always came up when I was talking to entrepreneurs there: “Why can’t we get invention and innovation in Russia?”
They were asking a legitimate question, because they already had IP laws on the books. They were much different from the laws in the Soviet period, which weren’t very strong. They were just wondering why invention wasn’t happening at the pace they thought it should be happening. So I said to them, “Well, you’ve got to have things like the rule of law. You’ve got to have personal security.”
At the time, I didn’t have any sort of empirical evidence that could show this. The conventional wisdom in the economics of innovation literature then was that if you have these strong IP laws, that would be sufficient to provide an incentive for patenting. I found that naïve.
So I wondered if there might be a historical experiment that might show this. One that would have an IP regime that stayed the same for some inventors but have other inventors subject to some sort of shock that had to do with violence or lack of rule of law. And I thought, “Well, that describes the United States. So maybe we can find this experiment in U.S. history.” You have a control and a treatment group. And the African Americans were going to be the treatment group.
IEEE Spectrum: How did you actually figure out which inventors were African American during your 1870-1940 study period, given that patent applications don’t list race?
Lisa D. Cook: I thought that was going to be easy, because there’s this emerging literature on Black names in economics. So I thought I could use the same techniques that my colleagues used at the time. I tried that. Then using census data, I came up with the first-ever list of historical black names. And it was of limited use. It barely identified anybody among the African American inventors.
So I had to try a new method. And that was finding all of the directories of scientists, engineers, and potential inventors that I could. In doing so, I found the survey of Henry Baker, the African American patent examiner in the early 1900s, who conducted surveys of patent agents and patent attorneys in 1900 and 1913.
That was very useful as a start. But it wasn’t perfect. So I had to extend it backwards and forwards and check everything, as well. I also checked things like obituaries, because one thing that I knew from all these directories that I was collecting was that they biased the sample towards famous people. So I thought I might get some equalization by just checking newspapers and checking obituaries. And I was able to recover some that way.
IEEE Spectrum: That sounds like a ton of work.
Lisa D. Cook: It was.
IEEE Spectrum: Would you briefly explain the key results?
Lisa D. Cook: The main results over the period are, first, that violence has an impact on all patenting. It has a significant and negative impact on Black patenting. So those who were targeted are going to be disproportionately affected by lynchings, riots, and segregation laws.
Second, the most valuable patents are the most affected by violence. And that’s not good news if you’re extrapolating this to an economy.
The next group of results would suggest that if White inventors had been subjected to the same type of violence, economic growth would have been a lot slower. Why? Because business investment would have been lower, and business investment is a key component of GDP. So we would have had fewer inventions and fewer patented inventions and therefore less business investment and therefore less growth.
IEEE Spectrum: Electrical patents were particularly affected. Why?
Lisa D. Cook: I separated patents into types of technological categories to see if one category was more affected by violence than others. And we did see that violence disproportionately affected—for that period—electrical patents, which would have been some of the most valuable.
You can imagine how that would be true: You really had to be up on the latest inventions and the latest patents to be able to be productive, to add an increment to the stock of knowledge. Electrical patents, at the time, would probably have taken more collaboration with other inventors and more trips to the patent attorney. And that was something that was cut off as a result of Plessy v. Ferguson [the disastrous 1896 U.S. Supreme Court decision that legitimized anti-Black laws passed by U.S. state legislatures beginning in the late 19th century]. You can imagine that if an inventor no longer had access to, for example, the main library, where patent registries and information about new inventions were and where inventors could gather, that would be detrimental to the free flow of information. If commercial business districts were segregated—there were no patent attorneys who were African Americans until the 1970s—that meant that you really didn’t have access to someone who could file and protect your invention.
IEEE Spectrum: What key events impacted African American innovation?
Lisa D. Cook: Plessy v. Ferguson in 1896 was a big one. 1899 was the peak for African American invention, and even using 2010 data [PDF} it was still the peak per capita for African American invention.
Scholars of constitutional law explain that the Plessy v. Ferguson Supreme Court rulings took two or three years to produce effects, for rulemaking to happen, and for laws to be passed. What we did see was a proliferation of laws after Plessy v. Ferguson in states, especially outside of the south, and that’s where patenting was happening. So I think it was largely Plessy v. Ferguson that led to this huge drop in patenting by African Americans that hasn’t yet recovered.
Blatant violence also had an effect. Before I did anything, I had looked at the time series of patents and I’d noticed several dips. One was 1899, and another one was in 1921. The first thing I did, being an economist of innovation, was try to see if the patent laws changed or if patents became more expensive. But the only thing I came up with was the Tulsa massacre. [In May and June 1921, a White mob attacked and destroyed a relatively wealthy African-American neighborhood in Tulsa, Oklahoma. Many in the mob had been deputized and armed by government officials, and the attack included aerial bombardment.] The local, state, and federal government failed African Americans so much in Tulsa that it had a sizeable effect on all African Americans. They felt terrorized at the time, and there was nobody who had their backs. So I think that that’s why 1921 stood out in the data, and I think there’s evidence to support that.
IEEE Spectrum: How much potential innovation was lost during that period, and how did you figure that out?
Lisa D. Cook: I extrapolated the trajectory from the pre-1900 trend and found that in the absence of violence and segregation, there should’ve been roughly 1100 patents at the time. That would’ve been the output of a mid-sized European country then. But what I found was 726 patents.
IEEE Spectrum: What does your research say generally about violence and innovation?
Lisa D. Cook: In the 2014 paper, what I did was to predict which lynchings (of a series of lynchings) would have the greatest impact on patenting, and it’s the first one. So that’s the one that you want to try to prevent. There are ways to do this, such as not letting white supremacist groups get out of control.
I think we don’t think enough about the conditions that inventors need to be productive, such that there can be a free flow of ideas. I think we put too much weight on the actual laws in place and not the environment in which they are operating. We have direct evidence that the conditions in which one is operating can make a huge difference, whether you’re adding to the stock of knowledge broadly or the stock of knowledge related to science and innovation.
IEEE Spectrum: What is holding back black entrepreneurship now?
Lisa D. Cook: I think that one of the big things that is holding back African American participation and women’s participation is workplace climate, frankly. There are three stages of innovation—education; training as an inventor, working in a lab, for example; and then the third phase, commercialization of the invention. There are well-known problems associated with workplace climate in each. There is systemic racism at every stage.
With respect to entrepreneurship at the very end, what I found in doing my research interviews is that networks matter a lot more than we have researched in economics. It is social networks, all types of networks that require engagement—like having an internship at an investment bank, or being a member of a golf club—that are needed to get inventions commercialized. Those networks result in introductions for venture capital funding, for example. And African Americans and women are often kept out of those networks. So it’s unsurprising that 1 percent of founders who received VC funding are Black.
As the COVID-19 pandemic began its explosive spread through the United States, tech workers were among the first to switch to working at home in mass numbers. By early March, before regional stay-at-home orders came into play, most tech professionals at Microsoft and Amazonhad switched to working at home, others would soon follow. Since then, Twitter announced that it would offer work-at-home as a permanent option to many of its employees, and Facebook also began planning for a large work-from-anywhere staff, but indicated that salaries would be adjusted to account for regional costs of living. On the other end of the spectrum, Appledeveloped a plan to bring employees back to the office in phases, starting this month.
Of course, with the world still in the midst of the coronavirus pandemic, nobody really knows exactly what the workplace will look like if, as expected, a vaccine proves protective and life in general returns to normal.
Blind, a company that operates private social networks for tech employees, reached out to its members several times during the past few months to find out just how remote work is going for them—and whether permanent remote work would open up the possibility of moving to a less tech-centric part of the country or world. I had a few additional questions, and Blind distributed those for me as a short survey in late June.
In that survey, we included an open-ended question about what tech professionals miss about office life. Some of the answers were a little surprising, and give a clue as to what may be lacking in the typical home office—like standing desks and giant whiteboards. The Spectrum/Blind survey received 2951 responses from 37 companies in the U.S., which Blind sorted by selected regions and companies.
Putting all this data together paints a picture of a tech workforce that is generally OK with staying at home. Facebook employees are the rare exception: Fewer may be looking for a permanent work-at-home option than CEO Mark Zuckerberg anticipates. By contrast, Apple employees, unlikely to be offered work-at-home options, would actually love the opportunity.
Should working at home turn permanent, some tech employees would consider relocating, particularly those who live in expensive areas. In a small survey with just over 1800 respondents, 70 percent of Bay Area residents would consider relocating—but half of those would only do so without a pay cut. In a separate poll of 2768 tech workers, Blind found that 66 percent of Bay Area tech workers would consider relocating, compared with 69 percent of tech professionals in New York and 63 percent in Seattle; the salary question wasn’t asked.
Separately, a recent survey of 2300 tech workers in the U.S., Canada, France, and the United Kingdom by Hired found that 53 percent of these tech workers would be inclined to move to an area with a lower cost of living if work from home became permanent. Some 40 percent generally supported cost of living adjustments in salaries, however, but only 32 percent would be willing to take that kind of pay cut according to the Hired survey. And, despite expressing an interest in cheaper areas, when asked to name the city to which they’d be most likely to relocate, their choices put New York, Seattle, and the San Francisco Bay Area on top.
Post-coronavirus, however, most do expect—indeed want—to go back to the office at least some of the time. According to Blind’s survey, the sweet spot is one to two days a week, followed by three to four days a week; those who would choose to give up either exclusively working at home or only working in the office were a far smaller group. Hired’s survey came up with similar numbers; half of the tech professionals responding want to return to their office at least once a week, but only seven percent want to go in every day.
Working at home does have its challenges, according to Blind’s survey. Most tech professional found working at home presented challenges, with distractions impacting their focus generally being the biggest problem. However, there were distinct differences among professionals at different companies, with Apple and Amazon employees, for example, struggling more with work/life balance, and Cisco employees feeling the negative effects of isolation.
What do tech professionals miss most about the office? Here’s where I asked an open-ended question, and got some interesting answers, with some regional differences.
It was no surprise that many respondents commented that they miss interaction with their colleagues, socializing, friendship, bonding, hallway conversations, and general chitchat. Many also missed the separation between home and work and more contained work hours. The physical environment at the office came into play as well—the space to spread out, the standing desks—and oh, those whiteboards! The free food, coffee, and other perks popped up more often in comments from Bay Area tech workers, though professionals in all regions missed lunches with their colleagues.
About that food, coffee, massages, and other perks: we asked our survey respondents if they think those will be coming back as offices restructure themselves post pandemic. Most think perks will make a comeback, though Bay Area tech workers are more confident about that than those in other regions. Interestingly, according to Hired’s survey, while people might be willing to give up those perks, 43 percent they would expect to be compensated for that loss in additional salary or other benefits.
It will be a while before we truly know whether the changes made to tech work during the pandemic are permanent, or when exactly we will return to normal, or a new normal. But companies are making plans to start bringing employees back.
For more than seven years, Blessin Varkey has headed the accessibility lab at Tamana, a New Delhi–based nonprofit that runs two schools and a skill development center for individuals with intellectual, learning, and developmental disabilities. At the lab, his team creates tech tools for sharpening the cognitive, behavioral, and social skills of students. Varkey has been invited to speak about accessibility at national as well as international forums such as the ACM SIGACCESS Conference on Computers and Accessibility, USA, and the Microsoft Enabling Opportunities Summit in Singapore. Initially though, translating his tech skills for the needs of people with disabilities posed a unique set of challenges.
When he introduced a tablet-based app, TOBY (Therapy Outcomes By You) Playpad, for the organization’s autism center, he faced skepticism from parents. “They said tablets won’t work,” says Varkey. “Their natural response to this would be that the child might throw it.” The app is packed with activities that help bolster cognitive and communication abilities of individuals with autism. Tamana collaborated with Deakin University, in Australia, one of the app’s developers, in May 2013, to create two prototypes—one in English and the other in Hindi—tailored to Indian culture.
In the end, the students adopted the technology well. “None of the students broke the iPads!” says Varkey. It was his first hallelujah moment in this field of work, as he was able to finally win the confidence of both parents and professional educators in the field.
Moreover, he had to “actually step out of the technology domain completely to understand how the disability sector works.” Varkey carefully studied students’ behavior—and that helped him design tools that meet the needs of particular groups. An app that works for a student with attention deficit hyperactivity disorder, may not work for an individual with autism spectrum disorder.
Capitalizing on this experience, Varkey’s team later developed an app called Hope for Tamana that uses Microsoft Kinect’s sensor to detect hand and foot motion and reflect it onscreen. Anuradha Dutta, a headmistress at one of Tamana’s centers, says the Hope app improves students’ joint-attention, locomotor, and math skills, among other things. “Most importantly, they learned to work under the pressure of time limits,” she adds.
Varkey’s work on Hope earned his team a prestigious social innovation award from the country’s leading IT trade association, NASSCOM. If young techies are interested in moving into this challenging but rewarding field, they need to study the sector, Varkey says. For example, in the field of accessibility, the key is to understand the needs of the different groups of students and the educators. He advises against the “I’m a technologist and I’ve got a solution for you” approach to tackling a problem. First, study the challenge, he says, and then explore the tech. Observing students helped Varkey fine-tune his tech solutions, and he wants app makers to do the same. “If a student is not working on the application [on a particular day], you make that note and report that [to the educator],” says Varkey. “Try to find from their educator if there was something wrong that had happened [to the student].” He reiterates that minor details like this affect the research of tech solutions.
The nonprofit sector, he says, can provide immense job satisfaction and be a viable alternative to the corporate life. “If [I] make some sort of change in one person’s life, that works for me,” he says.
Saurabh Srivastava, a former researcher at IBM Research India, who partnered with Varkey on Kinect-based apps, says that Varkey’s enthusiasm even trumped that of educators. Varkey is mulling future avenues and at the top of his list is pursuing a Ph.D. in accessibility. “That will help me spend more time on research and allow me to delve deeper into the tech aspect [of accessibility],” he says.
This article appears in the July 2020 print issue as “Profile: Blessin Varkey.”
“Spring Festival. New virus. Spreading person to person. This one has everything.” That’s the whole of an email message that I dashed off to a friend, a fellow China watcher, on 21 January, after reading a BBC story about China’s then-tiny COVID-19 epidemic. Something in that story rang alarm bells in my head.
As an entrepreneur, I’ve developed what I call my “Spidey sense”: From time to time I’ll read something, and then feel the hairs on the back of my neck start to rise. Perhaps that’s my amygdala signaling fear without my conscious mind registering why; I don’t know. I reckon this is common among startup entrepreneurs, who tend to have an uncanny ability to forecast the future based on a paucity of information.
Launching a startup requires equal parts faith, conviction, and sensitivity. You believe you can do it (faith) and have the skills to do it (conviction), yet you have to be ready to adapt—to pivot—as circumstances change (sensitivity). That last quality breeds entrepreneurs with good antennae, able to tune into the weak signals given off by the world around them.
Lest you think my short January email message shows particularly special amounts of entrepreneurial precognition, you should read the blog post that Tomas Pueyo, currently a vice president at Course Hero, published on 10 March on Medium. In “Coronavirus: Why You Must Act Now,” Pueyo tries to get his readers to understand the difference between linear growth—something we have experience with—and the exponential acceleration of viral pandemics. Our inability to comprehend exponential changes, which Pueyo aptly characterized as “gradually, and then suddenly,” accounts for most countries’ dangerously slow responses.
Nine days later, Pueyo followed up with a second long blog post, “The Hammer and the Dance,” which remains the best guide I know of to the months ahead. Pueyo predicts a global game of Whack-a-Mole, as the world locks down (the hammer), then finds a path back to normalcy, but with greater vigilance and variable amounts of social distancing to keep the pandemic under control (the dance).
At about the same time, Tokyo-based entrepreneur Patrick McKenzie looked beneath the seeming successes of the Japanese government’s ability to control the pandemic in February and March. Foreseeing disaster, he wrote a private report, publicly tweeting its cryptographically secure hash (thus providing a verifiable time stamp). Working quickly with a small group of like-minded people who had contacted him, he formalized those predictions and circulated a white paper. It argued that undetected transmissions of the virus from people with asymptomatic COVID-19 infections had begun to grow exponentially throughout Japan. That white paper helped to pressure many Japanese organizations to enact more timely and effective responses.
These entrepreneurs saw things many others could not. They then worked hard to turn their understanding into action. Pueyo’s original post got 40 million readers in its first week, while McKenzie’s white paper no doubt helped to save Japan from a pandemic as severe as those of Italy and Spain.
The past few months have made a mockery of the notion that the future will look much like the recent past. In this period of unprecedented change, we could all benefit from the cultivation of our Spidey senses. Somehow we must find the courage to stare into the chaotic abyss of the future, apply our minds, and accept what we might learn.
This article appears in the July 2020 print issue as “Spidey Senses.”
The collective thoughts of the interwebz
The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.