Category Archives: Computer Science
AVI WIGDERSON RECEIVES ACM A.M. TURING AWARD FOR GROUNDBREAKING INSIGHTS ON RANDOMNESS – PR Newswire
Leading Theoretical Computer Scientist Cited for Field-Defining Contributions
NEW YORK, April 10, 2024 /PRNewswire/ --ACM, the Association for Computing Machinery, today named Avi Wigderson as recipient of the 2023 ACM A.M. Turing Award for foundational contributions to the theory of computation, including reshaping our understanding of the role of randomness in computation, and for his decades of intellectual leadership in theoretical computer science.
The ACM A.M. Turing Award, often referred to as the "Nobel Prize of Computing," carries a $1 million prize.
Wigderson is the Herbert H. Maass Professor in the School of Mathematics at the Institute for Advanced Study in Princeton, New Jersey. He has been a leading figure in areas including computational complexity theory, algorithms and optimization, randomness and cryptography, parallel and distributed computation, combinatorics, and graph theory, as well as connections between theoretical computer science and mathematics and science.
The ACM A.M. Turing Award, often referred to as the "Nobel Prize of Computing," carries a $1 million prize with financial support provided by Google, Inc. The award is named for Alan M. Turing, the British mathematician who articulated the mathematical foundations of computing.
What is Theoretical Computer Science?Theoretical computer science is concerned with the mathematical underpinnings of the field. It poses questions such as "Is this problem solvable through computation?" or "If this problem is solvable through computation, how much time and other resources will be required?"
Theoretical computer science also explores the design of efficient algorithms. Every computing technology that touches our lives is made possible by algorithms. Understanding the principles that make for powerful and efficient algorithms deepens our understanding not only of computer science, but also the laws of nature. While theoretical computer science is known as a field that presents exciting intellectual challenges and is often not directly concerned with improving the practical applications of computing, research breakthroughs in this discipline have led to advances in almost every area of the fieldfrom cryptography and computational biology to network design, machine learning, and quantum computing.
Why is Randomness Important?Fundamentally, computers are deterministic systems; the set of instructions of an algorithm applied to any given input uniquely determines its computation and, in particular, its output. In other words, the deterministic algorithm is following a predictable pattern. Randomness, by contrast, lacks a well-defined pattern, or predictability in events or outcomes. Because the world we live in seems full of random events (weather systems, biological and quantum phenomena, etc.), computer scientists have enriched algorithms by allowing them to make random choices in the course of their computation, in the hope of improving their efficiency. And indeed, many problems for which no efficient deterministic algorithm was known have been solved efficiently by probabilistic algorithms, albeit with some small probability of error (that can be efficiently reduced). But is randomness essential, or can it be removed? And what is the quality of randomness needed for the success of probabilistic algorithms?
These, and many other fundamental questions lie at the heart of understanding randomness and pseudorandomness in computation. An improved understanding of the dynamics of randomness in computation can lead us to develop better algorithms as well as deepen our understanding of the nature of computation itself.
Wigderson's ContributionsA leader in theoretical computer science research for four decades, Wigderson has made foundational contributions to the understanding of the role of randomness and pseudorandomness in computation.
Computer scientists have discovered a remarkable connection between randomness and computational difficulty (i.e., identifying natural problems that have no efficient algorithms). Working with colleagues, Wigderson authored a highly influential series of works on trading hardness for randomness. They proved that, under standard and widely believed computational assumptions, every probabilistic polynomial time algorithm can be efficiently derandomized (namely, made fully deterministic). In other words, randomness is not necessary for efficient computation. This sequence of works revolutionized our understanding of the role of randomness in computation, and the way we think about randomness. This series of influential papers include the following three:
Importantly, the impact of these three papers by Wigderson goes far beyond the areas of randomness and derandomization. Ideas from these papers were subsequently used in many areas of theoretical computer science and led to impactful papers by several leading figures in the field.
Still working within the broad area of randomness in computation, in papers with Omer Reingold, Salil Vadhan, and Michael Capalbo, Wigderson gave the first efficient combinatorial constructions of expander graphs, which are sparse graphs that have strong connectivity properties. They have many important applications in both mathematics and theoretical computer science.
Outside of his work in randomness, Wigderson has been an intellectual leader in several other areas of theoretical computer science, including multi-prover interactive proofs, cryptography, and circuit complexity.
MentoringIn addition to his groundbreaking technical contributions, Wigderson is recognized as an esteemed mentor and colleague who has advised countless young researchers. His vast knowledge and unrivaled technical proficiencycoupled with his friendliness, enthusiasm, and generosityhave attracted many of the best young minds to pursue careers in theoretical computer science.
"It's important to point out that Avi Wigderson also received the Abel Prize, which is considered the most important honor for lifetime achievements in the field of mathematics," explained ACM President Yannis Ioannidis. "Being selected for the ACM A.M. Turing Award is a fitting follow-upas mathematics is foundational to computer science and Wigderson's work has connected a wide range of mathematical sub-areas to theoretical computer science. Wigderson is a towering intellectual force in theoretical computer science, an exciting discipline that attracts some of the most promising young researchers to work on the most difficult challenges. This year's Turing Award recognizes Wigderson's specific work on randomness, as well as the indirect but substantial impact he has had on the entire field of theoretical computer science."
"Avi Wigderson's work on randomness and other topics has set the agenda in theoretical computer science for the past three decades," explained Jeff Dean, Senior Vice President, Google. "From the earliest days of computer science, researchers have recognized that incorporating randomness was a way to design faster algorithms for a wide range of applications. Efforts to better understand randomness continue to yield important benefits to our field, and Wigderson has opened new horizons in this area. Google also salutes Wigderson's role as a mentor. His colleagues credit him with generating great ideas and research directions, and then motivating a new generation of smart young researchers to work on them. We congratulate Avi Wigderson on receiving the ACM A.M. Turing Awardcomputing's highest honor."
Biographical BackgroundSince 1999, Avi Wigderson has been the Herbert H. Maass Professor in the School of Mathematics at the Institute for Advanced Study in Princeton, New Jersey. Earlier, he was a Professor at the Hebrew University of Jerusalem and held visiting appointments at Princeton University, the University of California at Berkeley, IBM, and other institutions.
A graduate of The Technion Israel Institute of Technology, Wigderson earned MA, MSE, and PhD degrees in Computer Science from Princeton University. Wigderson's honors include the Abel Prize, the IMU Abacus Medal (previously known as the Nevanlinna Prize), the Donald E. Knuth Prize, the Edsger W. Dijkstra Prize in Distributed Computing, and the Gdel Prize. He is an ACM Fellow and a member of the U.S. National Academy of Sciences and the American Academy of Arts and Sciences.
About the ACM A.M. Turing AwardThe A.M. Turing Awardis named for Alan M. Turing, the British mathematician who articulated the mathematical foundations of computing, and who was a key contributor to the Allied cryptanalysis of the Enigma cipher during World War II. Since its inception in 1966, the Turing Award has honored the computer scientists and engineers who created the systems and their underlying theoretical foundations that have propelled the information technology industry.
About ACMACM, the Association for Computing Machinery, is the world's largest educational and scientific computing society, uniting computing educators, researchers, and professionals to inspire dialogue, share resources, and address the field's challenges. ACM strengthens the computing profession's collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.
SOURCE Association For Computing Machinery, Inc.
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AVI WIGDERSON RECEIVES ACM A.M. TURING AWARD FOR GROUNDBREAKING INSIGHTS ON RANDOMNESS - PR Newswire
Thermal camera senses breathing to improve exercise calorie estimates – EurekAlert
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New work by researchers at CMU and the Indian Institute of Technology (IIT) Gandhinagar shows that adding an inexpensive thermal camera to wearable devices could substantially improve how accurately they estimate calories burned.
Credit: Carnegie Mellon University
Any fitness buff will tell you that the estimates of calories burned made by smartphones, smartwatches and other wearable devices vary wildly. That's because these devices lack the sensors required to gather all the information they need to make accurate estimates.
But new work by researchers at Carnegie Mellon University and the Indian Institute of Technology (IIT) Gandhinagar shows that adding an inexpensive thermal camera to these devices could substantially improve accuracy.
Using the thermal camera to monitor a person's breathing rate and body temperature could reduce inaccuracies in energy expenditure estimates from nearly 40% with a current smartwatch to just under 6%, saidMayank Goel, an associate professor in the School of Computer Science'sSoftware and Societal Systems Department(S3D) andHuman-Computer Interaction Institute(HCII).
But respiratory and heart rates aren't sufficient because they fail to take individual physical and contextual differences into account, Goel said.
The gold standard for clinically measuring energy expenditure is a calorimeter, which uses heart rate, respiration and the concentration of carbon dioxide in exhaled breaths to determine calories burned. Wearables already do a reasonable job at measuring heart rate and adding a thermal camera would provide a means for measuring respiratory rate. No solution exists for measuring CO2 concentrations with a wearable device, but the thermal camera could measure body temperature.
"We lose the ability to measure the concentration of oxygen and CO2, but we gained temperature measurements," Goel said.
The combination of those three data points, with help from machine learning, enabled the researchers to develop a system,called JoulesEye, for estimating energy expenditure. They recruited 54 participants who either cycled or ran for 15 minutes. Their tests showed that JoulesEye could estimate burned calories with an error rate of just 5.8% when compared to a clinical calorimeter.
In addition to helping fitness buffs, JoulesEye could be used in sports training, as well as for monitoring people with chronic diabetes or cardiovascular disease.
A report on JoulesEye, co-authored by Goel, Adhikary, Sadeh and Nipun Batra, an assistant professor of computer science at IIT Gandhinagar, has been published in the Proceedings of the ACM Mobile, Wearable and Ubiquitous Technologies and will be presented in October at theUbiComp 2024conference in Melbourne, Australia.
The cost of incorporating a low-resolution thermal camera into wearable devices should be feasible, as these cameras are already available for $45 or less. But Goel says the team is working to incorporate an even lower-resolution thermal camera into the system, which could lower the price of the sensor. It would also reduce privacy concerns about a camera being routinely pointed at the user's face.
The team also hopes to reduce the amount of time the thermal camera must be aimed at the user's face. It now takes about 40 seconds to make the necessary measurements.
"Our goal is that the time it takes to check your watch should be enough time to get the information we need," Goel said.
"When people see these numbers, they make changes in their behavior and that can be troublesome if the numbers are wrong," Goel said. Someone who thinks they just burned 400 calories on the treadmill, for instance, may eat more calories throughout the day, even though their actual expenditure was closer to 200 calories.
"That is a huge problem," he added.
Monitoring respiration has been a longtime interest of Goel and his Smart Sensing for Humans (SMASH) Lab, which develops technologies for such applications as health sensing and activity recognition. For instance, he previously developed ways to measure breathing using several methods ranging from wireless router data to custom wearables that analyze chest movements.
While pursuing a different project, Maite Sadeh, a Cornell information sciences major who was a SMASH Lab summer intern, found reports on how respiration could be measured using a thermal camera to detect exhalations of hot air. Goel's group then realized that inhalation leads to evaporation around the lips and nostrils. Both of these signals can be captured by a thermal camera.
Rishiraj Adhikary, a Ph.D. student in computer science at IIT Gandhinagar who was also a lab intern via a Fulbright Scholarship, then found studies showing that respiration combined with heart rate could be used to measure energy expenditure.
Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.
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Thermal camera senses breathing to improve exercise calorie estimates - EurekAlert
Lawmakers narrow, advance bill on computer science, special education, reading and more – North Platte Telegraph
State Sen. Lynne Walz of Fremont, center left, meets with State Sen. Lou Ann Linehan of Elkhorn, left, and their respective legislative aides, Amanda Callaway and Ryan Yang, on the floor of the Legislature. April 9, 2024. (Zach Wendling/Nebraska Examiner)
LINCOLN A package of education-related bills is one step away from heading to the governor for approval, including the recruitment of special education teachers and training programs in reading and computer science.
State Sen. Lynne Walz of Fremont. April 5, 2024. (Zach Wendling/Nebraska Examiner)
Lawmakers advanced Legislative Bill 1284 on Tuesday from second-round debate while significantly reducing its fiscal impact through a plan to tap into existing funds for the proposed programs. The package of bills, spearheaded by State Sen. Lynne Walz of Fremont, would also set aside funds for dyslexia research grants and to put menstrual products in select schools.
This bill is so important to make sure that we are meeting the ever-changing needs of our students, teachers and parents, Walz said during debate.
Originally, LB 1284 included nine other bills with a cost of $1.25 million this fiscal year, followed by $17.3 million and $11.3 million in the next two.
The bill also came at a time when senators are running short on funds for their proposals.
Lawmakers adopted two amendments reducing LB 1284s General Fund impact, from the states main pocketbook, to administrative costs for the Teach in Nebraska Today Act, a teacher retention program.
The reductions lead to a General Fund impact of just under $150,000 in the next fiscal year and about $80,000 the year after.
State Sen. George Dungan of Lincoln. Feb. 14, 2024. (Zach Wendling/Nebraska Examiner)
The teaching act would be restructured as a grant program rather than loan repayment. Lawmakers kept the annual appropriation at $5 million rather than doubling it as originally proposed.
All other programs in LB 1284 would be funded through the Education Future Fund created last year ($4 million) or cash funds ($2.4 million).
LB 1284 originally included two bills aimed to bring more special education teachers to Nebraska, but one was removed Tuesday and the other was significantly reduced.
Walzs LB 1238, the Special Educators of Tomorrow Act, is no longer part of LB 1284. It would have provided scholarships and loans to individuals who work with disabilities as direct support professionals to become special education teachers.
A proposal from State Sen. George Dungan would extend eligibility for Nebraska Career Scholarships to include teaching in special education. As amended it would no longer provide forgivable loans to a handful of students studying special education each year.
State Sen. Lou Ann Linehan of Elkhorn, center, talks with State Sens. Lynne Walz of Fremont, at right, and Anna Wishart of Lincoln. April 9, 2024. (Zach Wendling/Nebraska Examiner)
State Sen. Lou Ann Linehan of Elkhorn originally sought to appropriate $10 million annually for reading improvement mentorship programs and to employ regional coaches to train teachers in kindergarten through third grade how to teach reading. That funding was reduced to $2 million.
Linehan said Tuesday that half of students will pick up how to read just through repetition, but the other half need more intensive help, such as a focus on phonics or vocabulary.
The funding in this bill will help the Department of Ed and the ESUs [educational service units] make sure that all our teachers have all the tools they need to make sure we increase reading, Linehan said.
Other proposals with reduced funding:
Linehan noted that she previously worked with former State Sen. Patty Pansing Brooks on third grade reading and dyslexia programs, and LB 1284 capped off her efforts. Both Linehan and Walz are barred from seeking reelection in the fall due to term limits.
This is kind of the last rah rah on those things, Linehan said.
LB 1284 advanced to a final round of debate via voice vote.
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Nebraska Lawmakers Narrow, Advance Bill On Computer Science, Special Education, Reading And More – Yankton Daily Press
LINCOLN, Neb. A package of education-related bills is one step away from heading to the governor for approval, including the recruitment of special education teachers and training programs in reading and computer science.
Lawmakers advanced Legislative Bill 1284 on Tuesday from second-round debate while significantly reducing its fiscal impact through a plan to tap into existing funds for the proposed programs. The package of bills, spearheaded by State Sen. Lynne Walz of Fremont, would also set aside funds for dyslexia research grants and to put menstrual products in select schools.
This bill is so important to make sure that we are meeting the ever-changing needs of our students, teachers and parents, Walz said during debate.
FISCAL IMPACT SIGNIFICANTLY REDUCED
Originally, LB 1284 included nine other bills with a cost of $1.25 million this fiscal year, followed by $17.3 million and $11.3 million in the next two.
The bill also came at a time when senators are running short on funds for their proposals.
Lawmakers adopted two amendments reducing LB 1284s General Fund impact, from the states main pocketbook, to administrative costs for the Teach in Nebraska Today Act, a teacher retention program.
The reductions lead to a General Fund impact of just under $150,000 in the next fiscal year and about $80,000 the year after.
The teaching act would be restructured as a grant program rather than loan repayment. Lawmakers kept the annual appropriation at $5 million rather than doubling it as originally proposed.
All other programs in LB 1284 would be funded through the Education Future Fund created last year ($4 million) or cash funds ($2.4 million).
SPECIAL EDUCATION PROPOSALS
LB 1284 originally included two bills aimed to bring more special education teachers to Nebraska, but one was removed Tuesday and the other was significantly reduced.
Walzs LB 1238, the Special Educators of Tomorrow Act, is no longer part of LB 1284. It would have provided scholarships and loans to individuals who work with disabilities as direct support professionals to become special education teachers.
A proposal from State Sen. George Dungan would extend eligibility for Nebraska Career Scholarships to include teaching in special education. As amended it would no longer provide forgivable loans to a handful of students studying special education each year.
State Sen. Lou Ann Linehan of Elkhorn originally sought to appropriate $10 million annually for reading improvement mentorship programs and to employ regional coaches to train teachers in kindergarten through third grade how to teach reading. That funding was reduced to $2 million.
Linehan said Tuesday that half of students will pick up how to read just through repetition, but the other half need more intensive help, such as a focus on phonics or vocabulary.
The funding in this bill will help the Department of Ed and the ESUs [educational service units] make sure that all our teachers have all the tools they need to make sure we increase reading, Linehan said.
Other proposals with reduced funding:
Walz sought to create a Computer Science and Technology Education Fund with an initial $1.5 million investment to provide teachers training and support to help students meet a related graduation requirement in those areas. The fund would instead begin at $1 million, and the state treasurer would add $500,000 annually to the fund if matching private donations are raised.
Linehan, who has dyslexia, sought to create a $1 million Dyslexia Research Grant Program to support Nebraska companies researching artificial-intelligence-based writing assistance for individuals with dyslexia, such as a group of University of Nebraska-Lincoln students. Instead, grants could be awarded up to $500,000.
Linehan noted that she previously worked with former State Sen. Patty Pansing Brooks on third grade reading and dyslexia programs, and LB 1284 capped off her efforts. Both Linehan and Walz are barred from seeking reelection in the fall due to term limits.
This is kind of the last rah rah on those things, Linehan said.
LB 1284 advanced to a final round of debate via voice vote.
Nebraska Examiner is part of States Newsroom, a nonprofit news network supported by grants and a coalition of donors as a 501c(3) public charity. Nebraska Examiner maintains editorial independence. Contact Editor Cate Folsom for questions: info@nebraskaexaminer.com. Follow Nebraska Examiner on Facebook and Twitter.
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Can the bias in algorithms help us see our own? – EurekAlert
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Algorithms can codify and amplify human bias, but algorithms also reveal structural biases in our society, says Carey Morewedge, a Questrom professor of marketing.
Credit: Photo courtesy of Carey Morewedge.
Algorithms were supposed to make our lives easier and fairer: help us find the best job applicants, help judges impartially assess the risks of bail and bond decisions, and ensure that healthcare is delivered to the patients with the greatest need. By now, though, we know that algorithms can bejust as biasedas the human decision-makers they inform and replace.
What if that werent a bad thing?
New research byCarey Morewedge, a Boston University Questrom School of Business professor of marketing and Everett W. Lord Distinguished Faculty Scholar, found that people recognize more of their biases in algorithms decisions than they do in their owneven when those decisions are the same. The research, publishing in theProceedings of the National Academy of Sciences, suggests ways that awareness might help human decision-makers recognize and correct for their biases.
A social problem is that algorithms learn and, at scale, roll out biases in the human decisions on which they were trained, says Morewedge, who also chairs Questroms marketing department. For example: In 2015, Amazon tested (andsoon scrapped) an algorithm to help its hiring managers filter through job applicants. They found that the program boosted rsums it perceived to come from male applicants, and downgraded those from female applicants, a clear case of gender bias.
But that same year, just39 percentof Amazons workforce were women. If the algorithm had been trained on Amazons existing hiring data, its no wonder it prioritized male applicantsAmazon already was. If its algorithm had a gender bias, its because Amazons managers were biased in their hiring decisions, Morewedge says.
Algorithms can codify and amplify human bias, but algorithms alsorevealstructural biases in our society, he says. Many biases cannot be observed at an individual level. Its hard to prove bias, for instance, in a single hiring decision. But when we add up decisions within and across persons, as we do when building algorithms, it can reveal structural biases in our systems and organizations.
Morewedge and his collaboratorsBegm eliktutan and Romain Cadario, both at Erasmus University in the Netherlandsdevised a series of experiments designed to tease out peoples social biases (including racism, sexism, and ageism). The team then compared research participants recognition of how those biases colored their own decisions versus decisions made by an algorithm. In the experiments, participants sometimes saw the decisions of real algorithms. But there was a catch: other times, the decisions attributed to algorithms were actually the participants choices, in disguise.
Across the board, participants were more likely to see bias in the decisions they thought came from algorithms than in their own decisions. Participants also saw as much bias in the decisions of algorithms as they did in the decisions of other people. (People generally better recognize bias in others than in themselves, a phenomenon called the bias blind spot.) Participants were also more likely to correct for bias in those decisions after the fact, a crucial step for minimizing bias in the future.
The researchers ran sets of participants, more than 6,000 in total, through nine experiments. In the first, participants rated a set of Airbnb listings, which included a few pieces of information about each listing: its average star rating (on a scale of 1 to 5) and the hosts name. The researchers assigned these fictional listings to hosts with names that were distinctively African American or white, based onprevious research identifying racial bias, according to the paper. The participants rated how likely they were to rent each listing.
In the second half of the experiment, participants were told about a research finding that explained how the hosts race might bias the ratings. Then, the researchers showed participants a set of ratings and asked them to assess (on a scale of 1 to 7) how likely it was that bias had influenced the ratings.
Participants saw either their own rating reflected back to them, their own rating under the guise of an algorithms, their own rating under the guise of someone elses, or an actual algorithm rating based on their preferences.
The researchers repeated this setup several times, testing for race, gender, age, and attractiveness bias in the profiles of Lyft drivers and Airbnb hosts. Each time, the results were consistent. Participants who thought they saw an algorithms ratings or someone elses ratings (whether or not they actually were) were more likely to perceive bias in the results.
Morewedge attributes this to the different evidence we use to assess bias in others and bias in ourselves. Since we have insight into our own thought process, he says, were more likely to trace back through our thinking and decide that it wasnt biased, perhaps driven by some other factor that went into our decisions. When analyzing the decisions of other people, however, all we have to judge is the outcome.
Lets say youre organizing a panel of speakers for an event, Morewedge says. If all those speakers are men, you might say that the outcome wasnt the result of gender bias because you werent even thinking about gender when you invited these speakers. But if you were attending this event and saw a panel of all-male speakers, youre more likely to conclude that there was gender bias in the selection.
Indeed, in one of their experiments, the researchers found that participants who were more prone to this bias blind spot were also more likely to see bias in decisions attributed to algorithms or others than in their own decisions. In another experiment, they discovered that people more easily saw their own decisions influenced by factors that were fairly neutral or reasonable, such as an Airbnb hosts star rating, compared to a prejudicial bias, such as raceperhaps because admitting to preferring a five-star rental isnt as threatening to ones sense of self or how others might view us, Morewedge suggests.
In the researchers final experiment, they gave participants a chance to correct bias in either their ratings or the ratings of an algorithm (real or not). People were more likely to correct the algorithms decisions, which reduced the actual bias in its ratings.
This is the crucial step for Morewedge and his colleagues, he says. For anyone motivated to reduce bias, being able to see it is the first step. Their research presents evidence that algorithms can be used as mirrorsa way to identify bias even when people cant see it in themselves.
Right now, I think the literature on algorithmic bias is bleak, Morewedge says. A lot of it says that we need to develop statistical methods to reduce prejudice in algorithms. But part of the problem is that prejudice comes from people. We should work to make algorithms better, but we should also work to make ourselves less biased.
Whats exciting about this work is that it shows that algorithms can codify or amplify human bias, but algorithms can also be tools to help people better see their own biases and correct them, he says. Algorithms are a double-edged sword. They can be a tool that amplifies our worst tendencies. And algorithms can be a tool that can help better ourselves.
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Proceedings of the National Academy of Sciences
Observational study
People
People see more of their biases in algorithms
12-Apr-2024
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Can the bias in algorithms help us see our own? - EurekAlert
Computer Science Professor Kenneth Kousen Gives Insights on AI and Emerging Technologies Trinity Tripod – Trinity Tripod
Lily Mellitz 26
Features Editor
In the rapidly evolving landscape of Artificial Intelligence (AI) and emerging technologies, understanding the implications and possibilities of these technologies is more crucial than ever. Kenneth Kousen, adjunct professor of Computer Science at Trinity College, recently shared his insights with the Tripod on the current state and future of AI and emerging technologies.
Kousen stands as a prominent figure in both the academic and professional world, blending entrepreneurship with a passion for teaching and a love for sharing knowledge. With an impressive academic journey that includes earning his Bachelors degree from Massachusetts Institute of Technology (MIT), Masters degrees from Princeton University and Rensselaer at Work and a Ph.D. from Princeton, Kousen brings a wealth of experience and expertise to his various roles.
Outside of academia, Kousen runs his own business: Kousen IT Incorporated. He frequently presents at the No Fluff Just Stuff U.S. conference series, and travels globally to speak at conferences around the world. He also runs a Youtube channel called Tales From the Jar Side where he shares insights, discussions and tutorials related to programming, technology and software development. Beyond podiums and webinars: Kousen has a total of six books to his name, including his most recent, Help Your Boss Help You, where he advises employees on how to develop healthy and productive relationships with their managers.
At Trinity, Kousen teaches courses in large scale application development, primarily in areas using Java (a coding language) and Open Source development. In one of his most popular classes Special Topics: Large Scale Development, students explore the complexities of handling big software projects. They learn about theories like how open-source projects function and different design patterns and get hands-on experience with practical skills.
Transitioning from his personal journey, Kousen delved into the dynamic evolution of technologies. Ive been in this field for a long time and Ive seen many major changes, Kousen said. The big one in my generation was the rise of the web. He went on to explain that while the internet previously existed, it was the introduction of user-friendly web browsers that revolutionized a shift in connectivity. Suddenly, complex networks became accessible to everyone, causing a wave of innovation and the birth of entire industries.
Something similar to that is happening now, Kousen said. AI is doing things weve never thought of before. One example Kousen gave was the significant time and effort efficiencies that AI can offer, especially for common, repetitive tasks where details might be overlooked.
When Im coding in Java, I know how to do that so I dont need a lot of AI assistance, Kousen said. However, in instances where he has worked with Python a coding language hes less experienced in he has often relied on AI to handle routine tasks, such as generating scripts to organize files. Kousen further elaborated on how AI could aid in software development practices, such as when committing code changes to a GitHub repository (a place where code for a project is stored and managed, allowing multiple developers to work together and track changes). AI tools can help crafting detailed commit messages, which not only document the changes made but also provide details into the reason behind them.
However, Kousen also stressed the importance of understanding the limitations of AI. He noted that some people are comparing these emerging AI tools to interns with access to vast resources but lacking in comprehensive understanding.
I wouldnt say thats quite right because interns still understand things, they just might need some explanations, Kousen said. These things [AI] dont understand anything.
Despite their impressive capabilities and creativity, AI algorithms primarily operate through pattern matching and lack true comprehension or depth. As an example, he shared about asking ChatGPT a simple math question: Whats nine plus seven? Its response of zero prompted his correction to 16, to which ChatGPT agreed. Yet, when asked about 10 plus 20, it returned 16.
ChatGPT doesnt understand, Kousen summarized. Theres no depth there. It learns by pattern matching with everything its been trained on.
Having spent the past year delving into the realms of AI and emerging technologies, Kousen offered several insights to current students preparing to enter the workforce.
If you are able to work with AI tools, you will have an advantage over students who are not able to work with the tools, he said. We can argue the ethics and whether its reasonable to try to replace people with AI, but the truth is that [AI is] not going away. They are here and they are going to get more pervasive, so my attitude is you might as well learn how to work with [them].
Kousen emphasized that the true concern isnt AI replacing human workers entirely, but rather the misconception among high-level managers that it could.
The danger time is now, when the managers especially non technical managers dont understand the limitations, Kousen explained. All they see is the pretty pictures and dazzling productivity and they dont realize the danger of AI.
Kousen illustrated this point with a scenario where a manager might believe AI could write Hollywood scripts better than professional script writers, or expect it to code whole systems more proficiently than professional coders. While AI excels at imitation, it struggles when it comes to creativity or adapting to unique situations, which could lead to serious problems down the line. In this scenario, Kousen recommended building a strong relationship with ones manager for personal well-being and self preservation within a company, especially in light of the increasing prominence of AI.
What becomes important is what you can offer to the manager, which is to be the technical expert that helps them assess what these technologies can and cannot do, Kousen said. Essentially, what is worth their money and what isnt.
The focus of education then is to make sure that the students get enough experience using these tools and trying them out to understand their limitations, Kousen said. And then they can offer to be the managers tech expert.
By gaining hands-on experience, students can confidently navigate discussions about the potential benefits and drawbacks of AI within their managers, proving to be valuable assets.
When asked how to remain valuable to ones managers, Kousen replied, The people who are successful in business are the ones who keep learning.
Kousen stressed the importance of embracing learning in order to maintain engagement and professionalism in any chosen field. He emphasized the value of viewing ones work not just as a job but as a profession; a career where one cares deeply about what they do and take pride in making a difference. He acknowledged that careers often take unexpected turns, but reassured that by approaching learning with a positive mindset, individuals will be able to adapt and thrive.
Kousens passion for software development shines through in his teaching, research and personal endeavors. His expertise on AI and emerging technologies not only equips his students with valuable skills and knowledge, but also instills in them the importance of critical thinking and awareness of the risks in the technological field. Serving as a guiding light for students and professionals alike, Kousen prompts all to contemplate the importance of growth, resilience and what it means to be human in the ever-changing realm of technology.
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UTC College Of Engineering And Computer Science Holds 7th Annual Technology Symposium – The Chattanoogan
Research projects by students from area high schools and Cleveland State Community College will compete alongside those of University of Tennessee at Chattanooga students at the seventh annual UTC Technology Symposium on April 15, and the public is invited to check them out.
Sponsored by the UTC College of Engineering and Computer Science, the daylong symposium will begin with a keynote address from UTC alumnus Greg Heinrich, TVA vice president of transmission operations and power supply.
Judges from more than 40 high-profile companiesTVA, Stantec, EPB, Amazon, American Express and Netflix among themwill review and assess the submissions, in addition to visiting with participating students. Project topics include identifying aging-related genes from muscle gene expression data; the performance of congressional stock portfolios: impact of socioeconomic status on education; and fraud detection in financial transactions using machine learning.
More information about the symposium and schedule of events is on the CECS website at utc.edu/tech-reg.
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EECS Students Place Third and Fourth at ICPC Competition – University of Arkansas Newswire
Dr. John Gauch
All of the EECS students that participated in the competition.
The International Collegiate Program Competition Regional was held on Feb. 24, 2024, in Fort Smith. The U of A's electrical engineering and computer science students paced third and fourth in the regional event level of the competition.
Alex Prosser, an EECS student participant, said the International Collegiate Program Competition is a programming competition meant for college students. There are about eight to 12 programming problems of different difficulty levels, and the team that solves the most problems wins.
Prosser said, "So, the entire world's competing in some way. The ICPC goes from a regional competition to a national one, and then to the world. We did not get that far this time. It is a programming competition that tests your ability to create algorithms, apply problem-solving and sharpen optimization."
Prosser explained that some of the problems required less skill than others. He said, "The difficulty is relative, depending on your experience. I found half of them easier to complete than the other ones."
Despite strong competition, the U of A teams placed third and fourth by solving five out of the 12 problems. "So, we solved the four easy ones, and we solved one of the medium ones, which seemed to be the general theme of the whole contest for our site," Prosser revealed.
For Prosser, competitive programming drives him to excel. "I love programming, so adding that competitive nature on top of it makes me want to learn more," he shared.
Reflecting on competitive programming, Prosser encouraged all U of A students in the Electrical Engineering and Computer Science program to try to compete: "I think all programming students should try competing. Honestly, just trying those smaller, easier problems is a place to start, just to see if this is something that interests you."
Congratulations to Rithyka Heng, Christopher Bayless and Ganner Whitmire for placing third, and to Gabriel Garcia, Jack Norris and Alex Prosser for placing fourth in the competition.
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EECS Students Place Third and Fourth at ICPC Competition - University of Arkansas Newswire
U.Md. launches new AI institute to think about AI going forward – WTOP
The University of Maryland has announced its new Artificial Intelligence Interdisciplinary Institute at Maryland, which will offer a major, minor and course options for all students.
Artificial intelligence is the future of technology, but the capabilities, and a lack of trust when it comes to Big Tech companies and their goals, means lots of people are wary. Will it take away our jobs? Will it be designed in ways that benefit people? Will it even consider the human impact?
But with a recognition that the technology is moving ahead, and has the capacity for good, the University of Maryland has announced its new Artificial Intelligence Interdisciplinary Institute at Maryland (AIM).
The program is housed in the Department of Computer Science for now, but a long list of new classes will be open to underclassmen in all academic disciplines. In fact, a new artificial intelligence major will be offered on two tracks one as a Bachelor of Science degree and one as a Bachelor of Arts degree.
One of the things we really want to do is make sure theres a sort of path to AI for any students, said Hal Daum, the programs inaugural director. Regardless of what your major is, we want to make sure that within your first year, or maybe two years of being a student here, you are sufficiently up to speed on modern AI technology. That you can use it for doing whatever career path you have, and whatever educational path you have.
Whether students go on the B.A. track or the B.S. track, a lot of the skills they learn will be the same, since its important to have that common base of knowledge about the subject.
But the B.A. will go much, much deeper on the humanistic side and the social science side of things, whereas the Bachelor of Science will go much, much deeper on the mathematical, algorithmic side of things, Daum told WTOP.
The program will launch with an understanding that a significant portion of the public has concerns about the future of AI and doesnt trust technology companies to do whats best for society.
I think part of what we need to do is both help people see the positives that come out, and structure future AI development and research, and so on, toward those positives, but also give people a realistic sense of what can go wrong, he said.
The goal is making sure the implications of their work is well understood before it goes too far in the wrong direction. Daum said he believes having students and faculty from the arts and humanities side of things can help shape that thinking.
I think the lack of having other voices in the room who understand people and understand peoples values and understand society, and how the world works, and so on, has led us to technologies that people are sort of rightfully wary of, because theyre not designed from the perspective of whats good for society or whats good for people, Daum said.
Universities, broadly speaking, are incredibly well positioned to do this type of work because we have humanists, we have social scientists. We have all of the people we need to talk to in order to really develop AI thats kind of good for everyone, he added.
Students who major in something that isnt related to STEM (or technology at all) will also be able to minor in artificial intelligence. He said the program has buy-in from all 12 deans across the university, since they understand how much of an impact this technology will have.
It really touches more or less every major on campus, if for no other reason than the nature of jobs might change, Daum said. What it means to be a journalist today might be different from what it means to be a journalist in five years. What it means to be an artist today might be different from what it means to be an artist in five years. Even what it means to be a computer scientist or a professor today is going to be different from what it means in five or 10 years.
Its expected that students will be able to start majoring in artificial intelligence soon if not this fall, then the following academic year. The new AIM program will have more than 100 faculty on its staff.
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U.Md. launches new AI institute to think about AI going forward - WTOP
Engineering and Computer Science Awards Presented at Convocation of Scholars – Arkansas State University
04/04/2024
JONESBORO The College of Engineering and Computer Science at Arkansas State University presented graduating student awards during a Convocation of Scholars awards ceremony Tuesday, according to Dr. Abhijit Bhattacharyya, dean of the college.
Jackson Chrestman of Jonesboro received the Chancellors Scholar Award and 4.0 Scholar Award as the colleges graduating senior with the highest overall grade point average. He will graduate with a Bachelor of Science degree in computer science.
Departmental awards were presented to the top graduating seniors within each of the academic degree programs. These awards include the Citizenship Award and the Outstanding Student Award.
The Citizenship Award is presented to a student within each degree program who demonstrates great leadership, character and departmental and community involvement.
The recipients are Shota Kato of Japan, Bachelor of Science (BS) in computer science; Nathan Raath of South Africa, BS in engineering technology; Zackary Overton of Bryant, BS in engineering management systems; Madison Walker of Tuckerman, Bachelor of Science in Civil Engineering (BSCE); Nicolas Palacios of Cabot, Bachelor of Science in Electrical Engineering (BSEE); Jeannette Strano of Cherokee Village, Bachelor of Science in Mechanical Engineering (BSME); Seth Moffett of Brinkley, BS in land surveying and geomatics.
The Outstanding Student Award is given to the individual with the highest GPA within each of the seven undergraduate degree plans.
The recipients are Jackson Chrestman of Jonesboro, BS in computer science; Cody Painter of Rowlett, Bachelor of Arts (BA) in computer science; Samuel Morris of El Paso, BS in engineering technology; Ryan Ahmad of Anthony, BS in engineering management systems; Luke Carden of Maumelle, BSCE; Elijah Mullins of Brookland, BSEE; Tuan Kiet Vuong of Vietnam, BSME; Morgan Diamond of Jonesboro, BSME, and Dylan Stewart of Monette, BS in land surveying and geomatics.
Convocation of Scholars events continue throughout April at A-State.
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