Artificial Intelligence Impact Assessments ("AIIAs"), a family of tools that provide structured processes to imagine the possible impacts of a proposed AI system, have become an increasingly popular proposal to govern AI systems. Recent efforts from government or private-sector organizations have proposed many diverse instantiations of AIIAs, which take a variety of forms ranging from open-ended questionnaires to graded score-cards. However, to date that has been limited evaluation of existing AIIA instruments. We conduct a classroom study (N = 38) at a large research-intensive university (R1) in an elective course focused on the societal and ethical implications of AI. We assign students to different organizational roles (for example, an ML scientist or product manager) and ask participant teams to complete one of three existing AI impact assessments for one of two imagined generative AI systems. In our thematic analysis of participants' responses to pre- and post-activity questionnaires, we find preliminary evidence that impact assessments can influence participants' perceptions of the potential risks of generative AI systems, and the level of responsibility held by AI experts in addressing potential harm. We also discover a consistent set of limitations shared by several existing AIIA instruments, which we group into concerns about their format and content, as well as the feasibility and effectiveness of the activity in foreseeing and mitigating potential harms. Drawing on the findings of this study, we provide recommendations for future work on developing and validating AIIAs.

Generative Artificial Intelligence (AI), particularly tools like OpenAI's popular ChatGPT, is reshaping the landscape of computer science research. Used wisely, these tools can boost the productivity of a computer research scientist. This paper provides an exploration of the diverse applications of ChatGPT and other generative AI technologies in computer science academic research, making recommendations about the use of Generative AI to make more productive the role of the computer research scientist, with the focus of writing new research papers. We highlight innovative uses such as brainstorming research ideas, aiding in the drafting and styling of academic papers and assisting in the synthesis of state-of-the-art section. Further, we delve into using these technologies in understanding interdisciplinary approaches, making complex texts simpler, and recommending suitable academic journals for publication. Significant focus is placed on generative AI's contributions to synthetic data creation, research methodology, and mentorship, as well as in task organization and article quality assessment. The paper also addresses the utility of AI in article review, adapting texts to length constraints, constructing counterarguments, and survey development. Moreover, we explore the capabilities of these tools in disseminating ideas, generating images and audio, text transcription, and engaging with editors. We also describe some non-recommended uses of generative AI for computer science research, mainly because of the limitations of this technology.

Many environmental remediation and energy applications (conversion and storage) for sustainability need design and development of green novel materials. Discovery processes of such novel materials are time taking and cumbersome due to large number of possible combinations and permutations of materials structures. Often theoretical studies based on Density Functional Theory (DFT) and other theories, coupled with Simulations are conducted to narrow down sample space of candidate materials, before conducting laboratory-based synthesis and analytical process. With the emergence of artificial intelligence (AI), AI techniques are being tried in this process too to ease out simulation time and cost. However tremendous values of previously published research from various parts of the world are still left as labor-intensive manual effort and discretion of individual researcher and prone to human omissions. AIMS-EREA is our novel framework to blend best of breed of Material Science theory with power of Generative AI to give best impact and smooth and quickest discovery of material for sustainability. This also helps to eliminate the possibility of production of hazardous residues and bye-products of the reactions. AIMS-EREA uses all available resources -- Predictive and Analytical AI on large collection of chemical databases along with automated intelligent assimilation of deep materials knowledge from previously published research works through Generative AI. We demonstrate use of our own novel framework with an example, how this framework can be successfully applied to achieve desired success in development of thermoelectric material for waste heat conversion.

Score-based generative models (SGMs) is a recent class of deep generative models with state-of-the-art performance in many applications. In this paper, we establish convergence guarantees for a general class of SGMs in 2-Wasserstein distance, assuming accurate score estimates and smooth log-concave data distribution. We specialize our result to several concrete SGMs with specific choices of forward processes modelled by stochastic differential equations, and obtain an upper bound on the iteration complexity for each model, which demonstrates the impacts of different choices of the forward processes. We also provide a lower bound when the data distribution is Gaussian. Numerically, we experiment SGMs with different forward processes, some of which are newly proposed in this paper, for unconditional image generation on CIFAR-10. We find that the experimental results are in good agreement with our theoretical predictions on the iteration complexity, and the models with our newly proposed forward processes can outperform existing models.

Late Friday afternoon, the famed artificial intelligence company OpenAI made a shocking announcement: Effective immediately, its board of directors was firing CEO Sam Altman, both from his leadership position and from the OpenAI board. CTO Mira Murati will assume Altman's duties as the company oversees a "leadership transition" and seeks a "permanent successor" for the top job. In addition, OpenAI president and co-founder Greg Brockman is "stepping down as chairman of the board," but will remain at the company and report to Murati during her tenure. In a tweeted statement, Altman wrote: "i loved my time at openai. it was transformative for me personally, and hopefully the world a little bit. It's a heckuva pre-weekend news dump from what is perhaps the best-known and most influential A.I. company of the decade, if not the century. After all, OpenAI's late-2022 releases of its generative-text bot, ChatGPT, and its automated imagemaker, DALL-E 2, did more than anything else to ...

The board of the company behind ChatGPT late on Friday fired OpenAI CEO Sam Altman -- to many, the human face of generative AI -- sending shock waves across the tech industry. OpenAI's Chief Technology Officer Mira Murati will serve as interim CEO, the company said, adding that it will conduct a formal search for a permanent CEO. The announcement blindsided many employees who discovered the abrupt management shuffle from an internal announcement and the company's public facing blog. OpenAI scheduled an emergency all-hands meeting to discuss the news with employees Friday afternoon, a person familiar with the matter said.

Until the dramatic departure of OpenAI's cofounder and CEO Sam Altman Friday, Mira Murati was its chief technology officer--but you could also call her as its minister of truth. In addition to heading the teams that develop tools such as ChatGPT and Dall-E, it's been her job to make sure those products don't mislead people, show bias, or snuff out humanity altogether. This interview was conducted in July 2023 for WIRED's cover story on OpenAI. It is being published today after Sam Altman's sudden departure to provide a glimpse at the thinking of the powerful AI company's new boss. Steven Levy: How did you come to join OpenAI?

OpenAI pushed out co-founder Sam Altman as chief executive officer, saying he wasn't being "consistently candid in his communications" with the artificial-intelligence company's board. The startup said Friday that its board concluded after a review that Altman's actions, which it didn't specify, were "hindering its ability to exercise its responsibilities." The company's statement, unusually candid for such a situation, said: "The board no longer has confidence in his ability to continue leading OpenAI."

OpenAI, the company behind ChatGPT, has announced that CEO and co-founder Sam Altman will immediately leave his role leading the company and step down from its board of directors. Altman was not "consistently candid in his communications with the board, hindering its ability to exercise its responsibilities," leading to the board losing confidence in his ability to lead the company, according to the announcement in a blog post on Nov. 17. Mira Murati, OpenAI's chief technology officer, will serve as interim CEO, the company said in the blog post. The company also announced that Greg Brockman, another OpenAI co-founder and president, would step down from his role as chairman of the board, although he would remain in his role as president, reporting to Murati. The sudden departure comes as a shock to the tech world.

The board no longer has confidence in his ability to continue leading OpenAI,