MIT study finds many large companies do not disclose AI risks
MIT Sloan said in a press release that a new working paper estimates 32% of the world's 100 largest companies and 62% of the 1,000 largest have not publicly acknowledged any AI risks. Researchers reviewed more than 500 annual reports, AI policies, and other public documents.
The researchers assessed disclosures against 24 categories in the MIT AI Risk Repository. Discrimination, weapons and cyberattacks, fraud and scams, privacy loss, and the devaluation of human creativity accounted for more than half of all acknowledgments.
None of the companies acknowledged risks involving power centralization or competition that could encourage deployment at the expense of safety. Among the 100 largest companies, 2% acknowledged AI misalignment, 1% acknowledged risks from interactions among multiple agents, 4% acknowledged dangerous capabilities, and 16% acknowledged AI security vulnerabilities.
Companies in sectors that experts rated as extremely vulnerable to a risk acknowledged that risk only 23% of the time. Among public companies that develop general purpose AI, 15% acknowledged misalignment risks, while 85% acknowledged discrimination risks.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like AI Policy Brief, Enterprise AI Brief or Daily AI Brief.
Also, consider following us on social media:
More from AI Safety
Nov 5 OpenAI Cyber Model Finds 948 Linux Kernel Privilege Escalation Flaws Nov 5 Network of 400 Apps Hid AI Nudify Tools From App Store Reviews Nov 5 Democrats Prioritize AI Investigations After Midterm Sweep Nov 5 OpenAI Finds GPT-6 Astra Underperforms on Safety Research Nov 4 AI political groups post mixed results in US midtermsMore from Enterprise
Nov 5 OpenAI Says Enterprise Sales Generate Most Revenue Nov 5 MercadoLibre Increases AI Spending by $30 Million From Prior Quarter Nov 4 Apple Cuts Daily AI Budget for Some Employees Nov 4 DocuSign acquires AI spending analysis company Suplari Nov 4 Further finds 69% of companies have not scaled AIEnterprise AI Brief
Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Riskonnect Finds Fewer Than Half of Companies Train Staff to Evaluate AI Outputs
CompTIA says enterprise AI is shifting toward risk management
IBM survey finds 80% of EMEA executives escalated AI incidents to senior leaders
BCG survey finds 40% of employees want more CEO transparency on AI
Deloitte Survey Finds 28% of Companies Report AI Revenue Gains
Daily AI Brief: the AI news that matters, in your inbox.