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Survey reveals executives' stance on human involvement in AI decision-making A recent survey conducted among 1,000 global executives sheds light on their perspective regarding the role of humans in AI decision-making. The survey, commissioned by Workday and conducted between April and May, shows that an overwhelming majority of business leaders, 93% to be precise, believe it is crucial for humans to maintain oversight when significant decisions are made using AI or machine learning. The survey highlights other concerns expressed by executives at the top levels. About 77% of respondents express apprehension regarding the timeliness and reliability of the underlying data that fuels AI systems. Moreover, only 29% of executives claim to be "very confident" that AI and machine learning are being ethically applied in business. The survey identifies the following as the most significant high-level risks associated with AI and ML implementation: 🔹Data security and privacy 🔹Accountability concerns 🔹Inability to measure return on investment 🔹Decision-making errors The potential impact on jobs is another concern raised by executives. Over half of the respondents believe that AI and machine learning could disrupt their employees' jobs. #AI#EthicsInAI

Meta accused of using pirated data for AI development The case of Kadrey et al. vs. Meta reveals troubling allegations about how Meta developed its AI models, including the use of pirated datasets from the shadow library LibGen. Plaintiffs accuse Meta of torrenting copyrighted works, stripping copyright management information, and using these datasets to train its Llama models—all with alleged approval from senior leadership, including CEO Mark Zuckerberg. Internal documents presented to the court show debates within Meta about the ethical and legal implications of these practices. Engineers expressed discomfort about torrenting pirated data on corporate laptops, while scripts were allegedly used to systematically remove copyright indicators to obscure the origins of the data. This case is part of a broader global reckoning about the role of copyrighted data in training generative AI. With courts in the US and beyond considering landmark cases, the legal and ethical framework surrounding AI development could change significantly. For Meta, the allegations pose not only legal risks but also reputational challenges as the company seeks to position itself as a leader in AI innovation. #AI#Copyright#EthicsInAI#AIRegulation

OECD’s Roadmap for AI Governance: Risks, Benefits, and Imperatives The OECD’s new report, "Assessing Potential Future AI Risks, Benefits, and Policy Imperatives", lays out a comprehensive framework for addressing AI’s transformative potential. It highlights AI’s capacity to revolutionize healthcare, education, and climate change mitigation, while simultaneously warning of risks like concentrated power, privacy breaches, and disinformation undermining democracy. Key policy actions proposed include: ✅ Establishing liability frameworks for AI harms. ✅ Promoting transparency and lifecycle risk management for high-risk systems. ✅ Investing in AI safety, alignment, and explainability research to ensure accountability and trustworthiness. This report is essential for aligning AI governance with societal values and preparing for its profound societal impact. #AIGovernance#OECD#EthicsInAI

U.S. Department of Justice Issues AI Compliance Guidelines: What Corporate Leaders Need to Know The U.S. Department of Justice (DoJ) has expanded its Evaluation of Corporate Compliance Programs (ECCP) to include the use of artificial intelligence (page four of the ECCP document here). This means companies deploying AI technologies must assess their potential for harm and ensure compliance or face significant legal consequences. Compliance officers now have a new challenge—ensuring their AI systems do not facilitate criminal activities or lead to unintended legal violations. Among the questions DoJ prosecutors will ask during investigations are: How does the company assess AI's impact on compliance with criminal laws? What steps are being taken to mitigate misuse by insiders? Companies are expected to monitor and test AI applications to prevent breaches, with the clear message that accountability lies with the company, not the AI. For corporate leaders, the takeaway is simple: AI governance and compliance are no longer optional—they're critical for avoiding legal pitfalls. #AICompliance#AIRegulation#EthicsInAI#LegalTech

OECD Publishes Key Papers on AI Governance(Part 2) More free online documents from OECD: ➡️A new dawn for public employment services ➡️Artificial intelligence and the changing demand for skills in Canada ➡️Artificial intelligence, data and competition ➡️Defining AI incidents and related terms ➡️The impact of AI on productivity, distribution & growth #AIGovernance#OECD#EthicsInAI#AIRegulation

OECD Publishes Key Papers on AI Governance The OECD has recently released a series of insightful papers on critical AI-related topics, offering a valuable resource for anyone invested in AI governance. These papers explore the evolving challenges and opportunities within AI, addressing topics such as ethics, transparency, and policy frameworks. For leaders looking to understand the complexities of AI regulation and how to align it with global best practices, this is a unique opportunity to deepen your knowledge. The papers are available for free online—download, engage, and contribute to shaping the future of AI governance: ➡️Measuring the demand for AI skills in the United Kingdom ➡️Regulatory approaches to Artificial Intelligence in finance ➡️The potential impact of AI on equity and inclusion in education ➡️AI, data governance and privacy ➡️Using AI to manage min. income benefits & unemployment assist ➡️Governing with Artificial Intelligence #AIGovernance#OECD#EthicsInAI#AIRegulation

AI in Crime: Soldier Arrested for Generating Child Pornography Using AI The recent arrest of an Army soldier in Alaska underscores the dark side of AI technology. Seth Herrera, stationed at Joint Base Elmendorf-Richardson, has been charged with using AI to generate child sexual abuse material (CSAM). This case reveals a disturbing new dimension in criminal activity, where AI tools are exploited to produce realistic, yet horrific, content. The US Department of Justice has made it clear that AI-generated CSAM will be pursued with the same vigor as traditionally created materials. This incident serves as a stark reminder that as technology advances, so must our commitment to safeguarding vulnerable populations. #AI#CyberLaw#EthicsInAI

Exploring the impact of AI on human well-being The World Health Organization (WHO) has raised an important concern regarding the use of artificial intelligence generated large language model tools in protecting and promoting human well-being. Platforms like ChatGPT, Bard, Bert, and others are gaining popularity due to their ability to imitate human communication, potentially supporting health-related needs. While the potential benefits are promising, WHO emphasizes the need for caution and careful examination of the associated risks. In this regard, WHO has provided guidance on the ethics and governance of AI for health. This guidance emphasizes six core principles: protecting autonomy, promoting human well-being, safety, and the public interest, ensuring transparency, explainability, and intelligibility, fostering responsibility and accountability, ensuring inclusiveness and equity, and promoting AI that is responsive and sustainable. Question to ponder: How can we ensure the responsible and ethical use of AI in healthcare while maximizing its potential to improve human well-being? #AI#HealthcareAI#EthicsInAI

OpenAI's hidden Influence on AI regulations In the world of AI and regulations, things aren't always as they seem. Recent revelations have shed light on OpenAI's lobbying efforts to weaken the AI Act, despite its public support for stronger guardrails. This behind-the-scenes maneuvering has sparked concerns and raised important questions about the balance between innovation and accountability. According to TIME, documents have surfaced indicating that OpenAI has actively advocated for provisions that would reduce the regulatory burden on the company. For instance, OpenAI argued against classifying its general purpose AI systems as "high risk." Such a classification would have subjected them to stringent legal requirements, ensuring a higher level of scrutiny and accountability. Surprisingly, OpenAI's lobbying appears to have had an impact. The final draft of the AI Act did not include language considering general purpose AI systems as inherently high risk. This omission has raised eyebrows and sparked a broader conversation about the influence of tech giants on AI regulations. These revelations bring forth an important question: Should AI companies have a say in shaping AI regulations, especially when their vested interests may conflict with public welfare? #AI#AIRegulations#EthicsInAI#OpenAI#AIAct

🇪🇺Deepfakes in the EU AI Regulation: Definition Challenges for Image Processing A critical analysis by Meding and Sorge highlights significant challenges in how the EU AI Regulation defines and regulates deepfakes. The lack of clear distinctions between legitimate image processing and deepfake creation leaves providers and users navigating a gray area, particularly given the complexity of transparency obligations. Key issues include: ✔️ Ambiguities in the definition of deepfakes, with no clear criteria for "standard editing functions" or "non-essential changes." ✔️ Confusion over differentiating changes at the pixel level versus visible alterations. ✔️ Modern tools like Google "Best Take" and Samsung’s editing features blur the boundaries of what qualifies as a deepfake. For companies working with AI-driven image processing, the risks are clear. To ensure compliance and avoid fines, businesses should prioritize implementing transparency mechanisms, such as content labeling, and conduct a detailed review of editing functionalities against regulatory standards. #AIRegulation#Deepfakes#EthicsInAI#DigitalTransparency

UK Regulation Proposals: What's on the Table? Hey there, legal minds! The Ada Lovelace Institute, a leading authority on AI ethics, has published a report analyzing the UK's approach to AI regulation. 📚 The report emphasizes three crucial 'tests' for the UK's AI regulation strategy. These tests aim to ensure comprehensive coverage in all contexts and effective enforcement to safeguard the public interest. The report calls for regulators to be adequately resourced, ensuring they have the power and means to effectively police and oversee the rapidly evolving AI landscape. With AI's potential to reshape society, robust regulation is essential. The Institute highlights the need for addressing AI-related risks sooner than originally planned. They argue that AI's potential harms require immediate attention, urging a proactive approach to protect individuals and communities. So, what are the key moments in the UK's AI regulation proposals? The document outlines measures to govern AI systems used in high-risk applications, such as healthcare and finance, to ensure safety, fairness, and accountability. To strike the right balance between innovation and responsibility, the report encourages policymakers to create transparent and trustworthy AI systems that people can rely on with confidence. #AIinLaw#LegalTech#AIRegulation#EthicsInAI#AdaLovelaceInstitute

🇺🇸Microsoft Takes Legal Action Against AI Abuse Scheme Microsoft has launched two lawsuits targeting an elaborate scheme to bypass safety guardrails in its generative AI systems. The first lawsuit is aimed at three individuals accused of running a "hacking-as-a-service" operation. These defendants allegedly created tools to exploit undocumented APIs, compromised legitimate customer accounts, and built a fee-based platform for generating harmful and illicit content. The second lawsuit targets ten individuals who were customers of this service. According to the complaints, the defendants’ platform provided detailed instructions on bypassing Microsoft’s restrictions, enabling the creation of prohibited content, including materials promoting harm or discrimination. Microsoft alleges the platform used stolen API keys and proxy servers to mimic legitimate requests, undermining the integrity of its Azure OpenAI systems. Both lawsuits, filed in Virginia, invoke the Computer Fraud and Abuse Act, the Digital Millennium Copyright Act, and other legal provisions. These cases underscore the ongoing challenges in securing generative AI platforms against abuse while maintaining their accessibility for ethical uses. #AIRegulation#Cybersecurity#EthicsInAI#Microsoft#AIAbuse