Stuart Russell calls for new approach for AI, a ‘civilization-ending’ technology

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Technology companies are racing to release increasingly powerful artificial intelligence (AI) tools. Some researchers claim this technology exhibits artificial general intelligence (AGI), a significant milestone where AI could independently learn and complete tasks like human beings. This technology has the power to change the world, said Stuart Russell, a UC Berkeley computer science professor and leading AI expert. It could improve quality of life for people across the planet or destroy civilization, he said. At an April 5 CITRIS Research Exchange and Berkeley AI Research Lab event, he urged both companies to pivot how they’re building AI and countries to regulate AI to ensure it furthers human interests.

Tool helps experts, students assess ethics of data science work in society

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Data science has unlocked new potential to help understand and address challenges like human health and climate change. But it can be challenging to know how to work ethically with data, especially when it has major impacts on society. Enter the Data Science Ethos tool by the Academic Data Science Alliance (ADSA). The alliance’s package of research-backed guidance and case studies show how to embed ethics into the lifecycle of data-driven projects. Students and experts can follow this framework to assess the effects of their choices at each stage of their work, from framing their research questions to interpreting and sharing their work.

From tort law to cheating, what is ChatGPT’s future in higher education?

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Berkeley News: It passed the bar exam, first with a mediocre score and then with a ranking among the top tier of newly minted lawyers. It scored better than 90% of SAT takers. It nearly aced the verbal section of the GRE — though it has room for improvement with AP Composition. In the months since the machine-learning interface ChatGPT debuted, hundreds of headlines and hot-takes have whirled about how artificial intelligence will overhaul everything from health care and business to legal affairs and shopping. But when it comes to higher education, reviews have been more mixed, a blend of upbeat and uneasy. Many have forecast the “death of the college essay,” though it’s still very much alive.

CDSS seeks undergraduate student nominations for new advisory committee

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UC Berkeley’s Division of Computing, Data Science, and Society (CDSS) is seeking undergraduate students to join a new advisory committee, the division announced today. The CDSS Undergraduate Advisory Committee will offer recommendations to the division on its operations, as it works to become the first new college at Berkeley in more than 50 years. Undergraduate student nominations, including self-nominations, are invited by April 11. “As we look forward to becoming a college, we welcome the opportunity to hear from students whose perspectives and ideas on the issues and services they care about will help build a stronger CDSS and campus community,” said Jennifer Chayes, associate provost of CDSS.

As tech company layoffs continue, Berkeley advisors share advice with students

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Thousands of UC Berkeley data science and computing students are preparing to graduate in May amidst a slew of technology company layoffs. Some are worried about finding a job. Berkeley advisors are urging expected graduates to take a beat and embrace a more nuanced job market view. They’re reminding students of what they have control over in their search and what they’ve already accomplished. And they’re telling students to give themselves grace. “This generation will have 12 plus jobs in their lifetime. I often emphasize to students that this is just the first one,” said Amanda Dillon, a Berkeley Data Science Undergraduate Studies advisor. “Students tend to really overwhelm themselves with expectations … [but] it’s just a stepping stone.”

Look for ‘who’s not at the table’ and other advice from female data scientists

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When Joyce Shen began teaching data science at UC Berkeley nearly a decade ago, she noticed a problem she’d also seen in industry. There were barely any women. The nascent data science field that would forever change how we live was being primarily developed by men, creating products that would shape society for decades. Today, due to intensive Berkeley recruitment efforts, she has seen the numbers in her classes change. “We have much more representation of students from all walks of life, including more women,” said Shen, a School of Information continuing lecturer and an investor focused on data and AI companies, at the Women in Data Science, Berkeley conference on March 7. That’s had an impact, she said. “Our discussions are much richer when we talk about ethics, when we talk about data quality.”

AI lectures at Berkeley to explore possibilities, implications of ChatGPT

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Since its launch last November, the artificial intelligence chatbot ChatGPT has been an international sensation, with people using the platform to do everything from writing essays, computer code, poems and research proposals to planning vacations, flirting with Tinder matches and creating malware. According to UC Berkeley computer scientist Ken Goldberg, the computer program’s facility with natural language — particularly its ability to consistently demonstrate creativity — is forcing many AI experts to rethink what machines may be capable of and even our understanding of intelligence. “ChatGPT may catalyze a paradigm shift,” said Goldberg.

Hany Farid testifies on Section 230 for ‘Platform Accountability: Gonzalez and Reform’

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On Wednesday, March 8, 2023, Hany Farid, professor in the UC Berkeley School of Information and Department of EECS testified at a hearing with the House Committee on the Judiciary and the Subcommittee on Privacy, Technology, and the Law entitled: “Platform Accountability: Gonzalez and Reform.” In his testimony, Farid points out how a platform such as YouTube’s recommendation system can lead to misinformation, extremism, and various other negative impacts. To fix this issue, he recommends clarifying Section 230’s role and protections to exclude such design flaws: “This can be accomplished,” he said, “by clarifying that Section 230 is intended to protect platforms from liability based exclusively on their hosting of user-generated content, and not – as it has been expanded to include – a platform’s design features that we now know is leading to significant harms to individuals, societies, and our very democracy.”

‘Eye-opening’: Education student sees the possibilities of data science

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Arlyn Moreno Luna and her family immigrated from Mexico to Oregon when she was 13 years old. Learning a new educational system and English with little support from her high school, she relied on her sister and friends to find her own way to college and beyond. Her experience fueled her to study access to higher education and equity issues related to first-generation, historically underrepresented and Latinx students. Today, as a fourth-year doctoral candidate at UC Berkeley’s School of Education, she examines topics like how a community college’s location impacts the attainment of associate degrees. Moreno Luna participated in the Data Science + Social Justice Workshop, a summer introductory data science program run by Berkeley’s D-Lab and Graduate Division. In this Q+A, she discusses her journey, why she’s interested in data science and how this field has expanded the possibilities of her higher education research. 

Yu wins 2023 COPSS Distinguished Achievement Award and Lectureship

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The Committee of Presidents of Statistical Societies (COPSS) has selected Bin Yu for the 2023 Distinguished Achievement Award and Lectureship (DAAL). Formerly known as the R. A. Fisher Award and Lectureship, the DAAL recognizes meritorious achievement and scholarship in statistical science and recognizes the highly significant impact of statistical methods on scientific investigations. She will deliver the DAAL Lecture at JSM in 2023 on veridical data science. Yu’s current research focuses on practice, algorithm, and theory of statistical machine learning, interpretable machine learning, and causal inference.