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AI agents operate with minimal safety guardrails as MIT study exposes lack of transparency

MIT's 2025 AI Agent Index analyzed 30 prominent AI agents and found alarming gaps in safety documentation. While 70% provide technical specs, only 19% disclose formal safety policies and fewer than 10% report external safety evaluations. The study reveals that as AI agents gain autonomy to browse the web, send emails, and execute complex tasks, developers remain reluctant to detail how they test for risks and exploits.

4 Sources

Yesterday

MIT Researchers Expose Hidden Biases and Personalities in Large Language Models

Researchers from MIT and UC San Diego have developed a method to identify and manipulate over 500 hidden concepts within large language models, including biases, personalities, and moods. The technique uses a Recursive Feature Machine algorithm to steer AI responses, improving performance while also exposing potential vulnerabilities like jailbreaking and hallucinations.

3 Sources

13 Feb 2026

AI Prosthetic Arm Study Finds One-Second Movement Speed Feels Most Natural to Users

Researchers used virtual reality to discover that AI-powered prosthetic arms feel most like part of the body when they move at a moderate pace of about one second. The study tested six different speeds and found that both overly fast and slow movements reduced body ownership and usability, revealing critical design insights for future autonomous prosthetics.

3 Sources

10 Feb 2026

AI Decodes Rules of Mysterious Roman Board Game After 1,700 Years of Silence

A mysterious limestone tablet discovered in the Netherlands has puzzled researchers for over a century. Now, artificial intelligence has cracked the code, revealing it as a blocking game played by Romans—centuries earlier than such games were thought to exist in Europe. The breakthrough demonstrates how AI simulations can unlock secrets of ancient cultures.

7 Sources

09 Feb 2026

MIT's AI Algorithm Unlocks Brainstem Imaging, Revealing Signs of Parkinson's and Brain Injury

Researchers from MIT, Harvard, and Massachusetts General Hospital have developed the BrainStem Bundle Tool (BSBT), an AI-powered software that automatically segments eight distinct nerve bundles in the brainstem using diffusion MRI. The tool revealed distinct patterns in patients with Parkinson's disease, multiple sclerosis, traumatic brain injury, and Alzheimer's, and tracked a coma patient's 7-month recovery.

2 Sources

AI chatbots fail to improve medical advice for patients, Oxford study reveals

A University of Oxford study published in Nature Medicine found that AI chatbots offer no advantage over internet searches when patients seek medical advice. Despite large language models achieving 94.9% accuracy in controlled tests, real-world human-AI interaction in healthcare revealed a troubling gap between AI potential and performance, with patients struggling to provide complete information and receiving inconsistent advice.

14 Sources

06 Feb 2026

New AI method tackles century-old challenge of identifying which dinosaur made which footprints

Researchers developed an AI-powered approach that analyzes eight distinct traits in dinosaur footprints to determine which species left them. The algorithm examined 1,974 footprint silhouettes spanning 150 million years, offering paleontologists an objective tool to solve a challenge that has sparked debate for generations.

2 Sources

University of Michigan's Prima AI model reads brain MRI scans in seconds with 97.5% accuracy

Researchers at University of Michigan developed Prima, an AI model that analyzes brain MRI scans and delivers diagnoses in seconds with up to 97.5% accuracy. Trained on over 220,000 MRI studies, Prima can prioritize emergency cases like strokes and brain hemorrhages, automatically alerting specialists. The system aims to address growing radiology shortages and reduce diagnostic delays across health systems.

4 Sources

03 Feb 2026

Apple researchers unlock faster, more natural-sounding Siri through new speech technology

Apple researchers have published a breakthrough study proposing a new text-to-speech approach that could dramatically improve Siri's performance. The research introduces Acoustic Similarity Groups (ASGs) to accelerate speech token generation while maintaining quality, potentially addressing long-standing complaints about the voice assistant's sluggish response time.

3 Sources

Contextual Errors Keep Medical AI From Reaching Its Full Potential in Clinical Settings

Harvard Medical School researchers have identified contextual errors as a major barrier preventing medical AI from transitioning into real-world clinical use. Despite thousands of models being developed, very few succeed in hospitals because they lack critical information about medical specialty, geographic location, and socioeconomic factors needed for accurate patient care.

2 Sources

02 Feb 2026

Anthropic study reveals AI chatbots distort reality in 1 of 1,300 conversations with Claude

Anthropic and University of Toronto researchers analyzed 1.5 million conversations with Claude and found troubling disempowerment patterns. Reality distortion occurred in one in 1,300 chats, while action distortion appeared in one in 6,000 conversations. The study reveals AI chatbots can undermine human autonomy by validating biases and influencing beliefs, with users paradoxically rating these distorting interactions more favorably.

3 Sources

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