RWDS Big Questions: how do we balance innovation and regulation in the world of AI? AI development is accelerating, while regulation moves more deliberately. That tension creates a core challenge: how do we maintain momentum without breaking the things that matter? The aim isn't to slow innovation unnecessarily, but to ensure progress happens at a pace that protects individuals and society. Responsible actors should not be disadvantaged -- yet safeguards are essential to maintain trust. For the latest video in our RWDS Big Questions series, our panel explores this delicate balance.

Two important things happened on January 20, 2025. In Washington, D.C., Donald Trump was inaugurated as President of the United States. In Hangzhou, China, a little-known Chinese firm called DeepSeek released R1, an AI model that industry watchers called a "Sputnik moment" for the country's AI industry. "Whether we like it or not, we're suddenly engaged in a fast-paced competition to build and define this groundbreaking technology that will determine so much about the future of civilization," said Trump later that year, as he announced his administration's AI action plan, which was titled "Winning the Race." There are many interpretations of what AI companies and their governments are racing towards, says AI policy researcher Lennart Heim: to deploy AI systems in the economy, to build robots, to create human-like artificial general intelligence.

The government at a Cabinet meeting Tuesday adopted its first basic plan on the development and utilization of artificial intelligence. The basic plan stipulates that Japan will create reliable AI while balancing technological innovation and risk management, with an aim to become a country that offers the best environment for AI development and utilization. Japan lags behind not only other advanced nations but also countries with smaller economies in terms of AI development, and the gap is becoming wider year by year, it warns. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right.

President Donald Trump speaks in the Roosevelt Room flanked by Masayoshi Son, Larry Ellison, and Sam Altman at the White House on January 21, 2025. President Donald Trump speaks in the Roosevelt Room flanked by Masayoshi Son, Larry Ellison, and Sam Altman at the White House on January 21, 2025. In case you missed it, 2025 was a big year for AI. It became an economic force, propping up the stock market, and a geopolitical pawn, redrawing the frontlines of Great Power competition. It had both global and deeply personal effects, changing the ways that we think, write, and relate.

A new Fox News poll shows 8 in 10 voters support careful artificial intelligence development to manage risks, while only 2 in 10 prefer rapid advancement.

This paper examines how international AI governance frameworks address gender issues and gender-based harms. The analysis covers binding regulations, such as the EU AI Act; soft law instruments, like the UNESCO Recommendations on AI Ethics; and global initiatives, such as the Global Partnership on AI (GPAI). These instruments reveal emerging trends, including the integration of gender concerns into broader human rights frameworks, a shift toward explicit gender-related provisions, and a growing emphasis on inclusivity and diversity. Yet, some critical gaps persist, including inconsistent treatment of gender across governance documents, limited engagement with intersectionality, and a lack of robust enforcement mechanisms. However, this paper argues that effective AI governance must be intersectional, enforceable, and inclusive. This is key to moving beyond tokenism toward meaningful equity and preventing reinforcement of existing inequalities. The study contributes to ethical AI debates by highlighting the importance of gender-sensitive governance in building a just technological future.

Sam Kirchner wants to save the world from artificial superintelligence. He's been missing for two weeks. B efore Sam Kirchner vanished, before the San Francisco Police Department began to warn that he could be armed and dangerous, before OpenAI locked down its offices over the potential threat, those who encountered him saw him as an ordinary, if ardent, activist. Phoebe Thomas Sorgen met Kirchner a few months ago at Travis Air Force Base, northeast of San Francisco, at a protest against immigration policy and U.S. military aid to Israel. Sorgen, a longtime activist whose first protests were against the Vietnam War, was going to block an entrance to the base with six other older women. Kirchner, 27 years old, was there with a couple of other members of a new group called Stop AI, and they all agreed to go along to record video on their phones in case of a confrontation with the police.

Amazon Employees for Climate Justice says that over 1,000 workers have signed a petition raising "serious concerns" about the company's "aggressive rollout" of artificial intelligence tools. Over 1,000 Amazon employees have anonymously signed an open letter warning that the company's allegedly "all-costs-justified, warp-speed approach to AI development" could cause "staggering damage to democracy, to our jobs, and to the earth," an internal advocacy group announced on Wednesday. Four members of Amazon Employees for Climate Justice tell WIRED that they began asking workers to sign the letter last month. After reaching their initial goal, the group published on Wednesday the job titles of the Amazon employees who signed and disclosed that more than 2,400 supporters from other organizations, including Google and Apple, have also joined in. Backers inside Amazon include high-ranking engineers, senior product leaders, marketing managers, and warehouse staff spanning many divisions of the company.

The widespread use of Large Language Models (LLMs) raises critical concerns regarding the unauthorized inclusion of copyrighted content in training data. Existing detection frameworks, such as DE-COP, are computationally intensive, and largely inaccessible to independent creators. As legal scrutiny increases, there is a pressing need for a scalable, transparent, and user-friendly solution. This paper introduce an open-source copyright detection platform that enables content creators to verify whether their work was used in LLM training datasets. Our approach enhances existing methodologies by facilitating ease of use, improving similarity detection, optimizing dataset validation, and reducing computational overhead by 10-30% with efficient API calls. With an intuitive user interface and scalable backend, this framework contributes to increasing transparency in AI development and ethical compliance, facilitating the foundation for further research in responsible AI development and copyright enforcement.

According to the theory of International Political Economy (IPE), states are often incentivized to rely on rather than constrain powerful corporations. For this reason, IPE provides a useful lens to explain why efforts to govern Artificial Intelligence (AI) at the international and national levels have thus far been developed, applied, and enforced unevenly. Building on recent work that explores how AI companies engage in geopolitics, this position paper argues that some AI workers can be considered actors of geopolitics. It makes the timely case that governance alone cannot ensure responsible, ethical, or robust AI development and use, and greater attention should be paid to bottom-up interventions at the site of AI development. AI workers themselves should be situated as individual agents of change, especially when considering their potential to foster Algorithmic Collective Action (ACA). Drawing on methods of Participatory Design (PD), this paper proposes engaging AI workers as sources of knowledge, relative power, and intentionality to encourage more responsible and just AI development and create the conditions that can facilitate ACA.