Fox News anchor Bret Baier has the latest on the Murdoch Children's Research Institute's partnership with the Gladstone Institutes for the'Decoding Broken Hearts' initiative on'Special Report.' The benefits of artificial intelligence (AI) in the medical space are ever-growing, but evidence suggests it can also come with risks. A new study by European researchers investigated how AI can change the behavior of endoscopists when conducting a colonoscopy, and how their performance dips when not using AI. The research followed clinicians at four endoscopy centers in Poland participating in the ACCEPT (Artificial Intelligence in Colonoscopy for Cancer Prevention) trial, where AI tools for polyp detection were introduced at the end of 2021. Colonoscopies at these centers were randomly selected to be administered with or without AI assistance.

The integration of artificial intelligence (AI) into the workplace is advancing rapidly, necessitating robust metrics to evaluate its tangible impact on the labour market. Existing measures of AI occupational exposure largely focus on AI's theoretical potential to substitute or complement human labour on the basis of technical feasibility, providing limited insight into actual adoption and offering inadequate guidance for policymakers. To address this gap, we introduce the AI Startup Exposure (AISE) index-a novel metric based on occupational descriptions from O*NET and AI applications developed by startups funded by the Y Combinator accelerator. Our findings indicate that while high-skilled professions are theoretically highly exposed according to conventional metrics, they are heterogeneously targeted by startups. Roles involving routine organizational tasks-such as data analysis and office management-display significant exposure, while occupations involving tasks that are less amenable to AI automation due to ethical or high-stakes, more than feasibility, considerations -- such as judges or surgeons -- present lower AISE scores. By focusing on venture-backed AI applications, our approach offers a nuanced perspective on how AI is reshaping the labour market. It challenges the conventional assumption that high-skilled jobs uniformly face high AI risks, highlighting instead the role of today's AI players' societal desirability-driven and market-oriented choices as critical determinants of AI exposure. Contrary to fears of widespread job displacement, our findings suggest that AI adoption will be gradual and shaped by social factors as much as by the technical feasibility of AI applications. This framework provides a dynamic, forward-looking tool for policymakers and stakeholders to monitor AI's evolving impact and navigate the changing labour landscape.

The spread and rapid development of AI-related technologies are influencing many aspects of our daily lives, from social to educational, including the labour market. Many researchers have been highlighting the key role AI and technologies play in reshaping jobs and their related tasks, either by automating or enhancing human capabilities in the workplace. Can we estimate if, and to what extent, jobs and related tasks are exposed to the risk of being automatized by state-of-the-art AI-related technologies? Our work tackles this question through a data-driven approach: (i) developing a reproducible framework that exploits a battery of open-source Large Language Models to assess current AI and robotics' capabilities in performing job-related tasks; (ii) formalising and computing an AI exposure measure by occupation, namely the teai (Task Exposure to AI) index. Our results show that about one-third of U.S. employment is highly exposed to AI, primarily in high-skill jobs (aka, white collars). This exposure correlates positively with employment and wage growth from 2019 to 2023, indicating a beneficial impact of AI on productivity. The source codes and results are publicly available, enabling the whole community to benchmark and track AI and technology capabilities over time.

When most people think of the connection between technology and jobs, they think of robots and automation taking over relatively unskilled jobs like factory work. And thus, the biggest toll from these technological advances would be on already hard-hit manufacturing regions of the Rust Belt. But a new wave of developments in artificial intelligence may have a greater effect on high-skilled jobs and high-tech knowledge regions. The study by Mark Muro, Jacob Whiton, and Robert Maxim takes a close look at the potential of artificial intelligence--or AI--to automate tasks that until now have required human intelligence and decision-making. As they put it: "Unlike robotics (associated with the factory floor) and computers (associated with routine office activities), AI has a distinctly white-collar bent."

One of the complications, and opportunities, confronting the cyber security industry is that the cyber threat may be escalating beyond the capacity of a human-centric response. Consider for instance the remarks of the outgoing chief of the Department of Defense, that "given the volume [of attacks] and where I see the threat moving it will be impossible for humans by themselves to keep pace." The DoD currently finds itself amidst a $1.6 billion project of centralizing its hundreds of separate firewalls into a unified system, the end purpose being to enable effective integration of artificial intelligence capabilities. While this DoD example is an isolated one, it nonetheless epitomizes the human limitation in countering the cyber threat, which is primarily a digitalized, computer-driven hazard. As Benedict Cumberbatch playing Alan Turing in The Imitation Game quipped, "our problem is that we're trying to beat [enigma] with men. What if only a machine can defeat another machine?"