You’re a Computer Science Major. Don’t Panic.; The New York Times, November 12, 2025

 Mary Shaw and Michael Hilton, The New York Times ; You’re a Computer Science Major. Don’t Panic.

"The future of computer science education is to teach students how to master the indispensable skill of supervision.

Why? Because the speed and efficiency of using A.I. to write code is balanced by the reality that it often gets things wrong. These tools are designed to produce results that look convincing, but may still contain errors. A recent survey showed that over half of professional developers use A.I. tools daily, but only about one-third trust their accuracy. When asked what their greatest frustration is about using A.I. tools, two-thirds of respondents answered, “A.I. solutions that are almost right but not quite.”

There is still a need for humans to play a role in coding — a supervisory one, where programmers oversee the use of A.I. tools, determine if A.I.-generated code does what it is supposed to do and make essential repairs to defective code."

ACM FAccT ACM Conference on Fairness, Accountability, and Transparency; June 23-26, 2025, Athens, Greece

 

ACM FAccT

ACM Conference on Fairness, Accountability, and Transparency

A computer science conference with a cross-disciplinary focus that brings together researchers and practitioners interested in fairness, accountability, and transparency in socio-technical systems.

"Algorithmic systems are being adopted in a growing number of contexts, fueled by big data. These systems filter, sort, score, recommend, personalize, and otherwise shape human experience, increasingly making or informing decisions with major impact on access to, e.g., credit, insurance, healthcare, parole, social security, and immigration. Although these systems may bring myriad benefits, they also contain inherent risks, such as codifying and entrenching biases; reducing accountability, and hindering due process; they also increase the information asymmetry between individuals whose data feed into these systems and big players capable of inferring potentially relevant information.

ACM FAccT is an interdisciplinary conference dedicated to bringing together a diverse community of scholars from computer science, law, social sciences, and humanities to investigate and tackle issues in this emerging area. Research challenges are not limited to technological solutions regarding potential bias, but include the question of whether decisions should be outsourced to data- and code-driven computing systems. We particularly seek to evaluate technical solutions with respect to existing problems, reflecting upon their benefits and risks; to address pivotal questions about economic incentive structures, perverse implications, distribution of power, and redistribution of welfare; and to ground research on fairness, accountability, and transparency in existing legal requirements."