Many countries are exploring how artificial intelligence might help with everything from processing taxes to determining welfare benefits. But a survey shows citizens are not as enthusiastic as their governments – and this can create real risks for democracy. "Focusing only on short-term efficiency gains and shiny technology risks triggering public backlash and contributing to a long-term decline in democratic trust and legitimacy," says Alexander Wuttke at the Ludwig Maximilian University of Munich in Germany. Wuttke and his colleagues asked around 1200 people in the UK to share their feelings about government actions where either a human or an AI handled the task. These hypothetical scenarios included processing tax returns, approving or rejecting welfare applications and making risk assessments about whether defendants should be eligible for bail. Some people were only told about how AI could improve government efficiency – but others learned about both AI-related benefits and risks.

The use of chatbots equipped with artificial intelligence (AI) in educational settings has increased in recent years, showing potential to support teaching and learning. However, the adoption of these technologies has raised concerns about their impact on academic integrity, students' ability to problem-solve independently, and potential underlying biases. To better understand students' perspectives and experiences with these tools, a survey was conducted at a large public university in the United States. Through thematic analysis, 262 undergraduate students' responses regarding their perceived benefits and risks of AI chatbots in education were identified and categorized into themes. The results discuss several benefits identified by the students, with feedback and study support, instruction capabilities, and access to information being the most cited. Their primary concerns included risks to academic integrity, accuracy of information, loss of critical thinking skills, the potential development of overreliance, and ethical considerations such as data privacy, system bias, environmental impact, and preservation of human elements in education. While student perceptions align with previously discussed benefits and risks of AI in education, they show heightened concerns about distinguishing between human and AI generated work - particularly in cases where authentic work is flagged as AI-generated. To address students' concerns, institutions can establish clear policies regarding AI use and develop curriculum around AI literacy. With these in place, practitioners can effectively develop and implement educational systems that leverage AI's potential in areas such as immediate feedback and personalized learning support. This approach can enhance the quality of students' educational experiences while preserving the integrity of the learning process with AI.

As AI systems quickly improve in both breadth and depth of performance, they lend themselves to creating increasingly powerful and realistic agents, including the possibility of agents modeled on specific people. We anticipate that within our lifetimes it may become common practice for people to create a custom AI agent to interact with loved ones and/or the broader world after death. We call these generative ghosts, since such agents will be capable of generating novel content rather than merely parroting content produced by their creator while living. In this paper, we first discuss the design space of potential implementations of generative ghosts. We then discuss the practical and ethical implications of generative ghosts, including potential positive and negative impacts on individuals and society. Based on these considerations, we lay out a research agenda for the AI and HCI research communities to empower people to create and interact with AI afterlives in a safe and beneficial manner.

California Gov. Gavin Newsom on Wednesday signed an executive order directing state agencies to examine the benefits and risks of artificial intelligence that can generate text, images and other content. The executive order sets the stage for potential regulation around what's known as generative AI technology, which has already raised concerns about misinformation, plagiarism, bias and child safety. The governor and California lawmakers thus far have been cautious about regulating technology they might not fully understand and hindering business innovations that fuel the state's economy. "We recognize both the potential benefits and risks these tools enable. We're neither frozen by the fears nor hypnotized by the upside," Newsom said in a statement.

AI is transforming the business world, creating enormous benefits for firms and customers. John Deere is one example of a company that is using AI to improve its products and services. The coming wave of foundation models is likely to turn a lot more AI boring, with applications that range from computer programming to story-telling. However, businesses must tread carefully as they deploy more AI, as foundation models can sometimes reflect humanity's darker side. The age of "boring AI" will be anything but Business

Remote working environments and social distancing have caused people to become more comfortable with technology and developing employment relationships remotely, rather than face-to-face. Bringing artificial intelligence (AI) into the equation can add an additional layer of complexity and potential pitfalls to the human resources industry. In this webinar, Lee Moylan and Widener University Delaware School of Law law student Kamia McDaniels will explore AI and the algorithms behind it, the applications of AI in the hiring process and the pros and cons of utilizing it -- particularly, its impacts on diversity. This complimentary program will qualify for 1 hour of PA CLE ethics credit.* Please register here to access this Zoom webinar.

Kevin Markarian is the cofounder of Roopler, an AI-driven lead generation platform built for the real estate industry. Artificial intelligence is rapidly upending how people do business across industries, and yet skeptics still abound. But is there really a reason to fear AI? AI will change how we work and do business, and its impact is already being felt. Still, that doesn't mean it is something to fear. On the contrary, business managers and leaders who embrace AI and harness its potential now have everything to gain.

As foundation models (e.g., GPT-3, PaLM, DALL-E 2) become more powerful and ubiquitous, the issue of responsible release becomes critically important. In this blog post, we use the term release to mean research access: foundation model developers making assets such as data, code, and models accessible to external researchers. Deploying to users for testing and collecting feedback (Ouyang et al. 2022; Scheurer et al. 2022; AI Test Kitchen) and deploying to end users in products (Schwartz et al. 2022) are other forms of release that are out of scope for this blog post. Foundation model developers presently take divergent positions on the topic of release and research access. For example, EleutherAI, Meta, and the BigScience project led by Hugging Face embrace broadly open release (see EleutherAI's statement and Meta's recent release). In contrast, OpenAI advocates for a staged release and currently provides the general public with only API access; Microsoft also provides API access, but to a restricted set of academic researchers.

But instead of doomsday scenarios with humanity cowering at the feet of our robot overlords, AI has emerged as one of the most significant forces behind …

In December 2017, AlphaZero, a chess-playing, artificial intelligence (AI) developed by Google, defeated Stockfish 8, the reigning world champion program at that time. AlphaZero calculates around 80,000 moves per second, according to The Guardian. Yet, out of 100 matches, AlphaZero won 28 and tied 72. Stockfish's open-source algorithm has been continually tweaked by human input over the years. The New Yorker reports that coders suggest an idea to update the algorithm, and the two versions are then pitted against each other for thousands of matches to see which comes out on top. Google claims that AlphaZero's machine learning algorithm had no human input beyond the programming of the basic rules of chess.