# Marzyeh Ghassemi

Published articles for Marzyeh Ghassemi.

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## The benefits of medical AI assistance vary based on user expertise

DevFeed: [The benefits of medical AI assistance vary based on user expertise](<https://devfeed.tech/articles/the-benefits-of-medical-ai-assistance-vary-based-on-user-expertise-37964.md>)

Original publisher: [Read original article](<https://news.mit.edu/2026/medical-ai-assistance-benefits-vary-based-on-user-expertise-0804>)

Author: Adam Zewe | MIT News

Published: 2026-08-04T09:00:00Z

Content type: news

Language: en

Sources: [MIT AI News](<https://devfeed.tech/sources/mit-ai-news.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Human-AI evaluation](<https://devfeed.tech/topics/human-ai-evaluation.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>), [AI Chat](<https://devfeed.tech/topics/ai-chat.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [bias](<https://devfeed.tech/tags/bias.md>), [computer-science-and-technology](<https://devfeed.tech/tags/computer-science-and-technology.md>), [decision-making](<https://devfeed.tech/tags/decision-making.md>), [dermatological-diagnosis](<https://devfeed.tech/tags/dermatological-diagnosis.md>), [diagnosing-skin-disease](<https://devfeed.tech/tags/diagnosing-skin-disease.md>), [diagnostics](<https://devfeed.tech/tags/diagnostics.md>), [electrical-engineering-and-computer-science-eecs](<https://devfeed.tech/tags/electrical-engineering-and-computer-science-eecs.md>), [explainability](<https://devfeed.tech/tags/explainability.md>), [explainable-ai](<https://devfeed.tech/tags/explainable-ai.md>), [health-care](<https://devfeed.tech/tags/health-care.md>), [human-computer-interaction](<https://devfeed.tech/tags/human-computer-interaction.md>), [institute-for-medical-engineering-and-science-imes](<https://devfeed.tech/tags/institute-for-medical-engineering-and-science-imes.md>), [jameel-clinic](<https://devfeed.tech/tags/jameel-clinic.md>), [laboratory-for-information-and-decision-systems-lids](<https://devfeed.tech/tags/laboratory-for-information-and-decision-systems-lids.md>), [large-language-model](<https://devfeed.tech/tags/large-language-model.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [marzyeh-ghassemi](<https://devfeed.tech/tags/marzyeh-ghassemi.md>), [medicine](<https://devfeed.tech/tags/medicine.md>), [research](<https://devfeed.tech/tags/research.md>), [technology-and-society](<https://devfeed.tech/tags/technology-and-society.md>), [users](<https://devfeed.tech/tags/users.md>)

### AI overview

A study found that AI assistance improved skin-disease diagnosis for non-experts and clinicians, but explainability affected users differently. Non-experts often deferred to LLM-based explanations even when the AI was wrong, while clinicians performed best with the model's prediction alone.

### Source excerpt

Study finds non-experts deferred to LLM-based diagnostic assistance, even when it was wrong, while clinicians caught AI errors.

## New method aims to keep kids safe from illegal AI-generated content

DevFeed: [New method aims to keep kids safe from illegal AI-generated content](<https://devfeed.tech/articles/new-method-aims-to-keep-kids-safe-from-illegal-ai-generated-content-37976.md>)

Original publisher: [Read original article](<https://news.mit.edu/2026/new-method-keeps-kids-safe-from-illegal-ai-generated-content-0713>)

Author: Adam Zewe | MIT News

Published: 2026-07-13T04:00:00Z

Content type: news

Language: en

Sources: [MIT AI News](<https://devfeed.tech/sources/mit-ai-news.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [ai safety](<https://devfeed.tech/topics/ai-safety.md>), [AI Research](<https://devfeed.tech/topics/ai-research.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-deepfakes](<https://devfeed.tech/tags/ai-deepfakes.md>), [ai-safety](<https://devfeed.tech/tags/ai-safety.md>), [algorithms](<https://devfeed.tech/tags/algorithms.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [ashia-wilson](<https://devfeed.tech/tags/ashia-wilson.md>), [computer-science-and-technology](<https://devfeed.tech/tags/computer-science-and-technology.md>), [csam](<https://devfeed.tech/tags/csam.md>), [ethics](<https://devfeed.tech/tags/ethics.md>), [generative](<https://devfeed.tech/tags/generative.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [human-computer-interaction](<https://devfeed.tech/tags/human-computer-interaction.md>), [institute-for-medical-engineering-and-science-imes](<https://devfeed.tech/tags/institute-for-medical-engineering-and-science-imes.md>), [laboratory-for-information-and-decision-systems-lids](<https://devfeed.tech/tags/laboratory-for-information-and-decision-systems-lids.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [marzyeh-ghassemi](<https://devfeed.tech/tags/marzyeh-ghassemi.md>), [mit-schwarzman-college-of-computing](<https://devfeed.tech/tags/mit-schwarzman-college-of-computing.md>), [models](<https://devfeed.tech/tags/models.md>), [online-child-safety](<https://devfeed.tech/tags/online-child-safety.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [privacy](<https://devfeed.tech/tags/privacy.md>), [public-health](<https://devfeed.tech/tags/public-health.md>), [research](<https://devfeed.tech/tags/research.md>), [safety](<https://devfeed.tech/tags/safety.md>), [school-of-engineering](<https://devfeed.tech/tags/school-of-engineering.md>), [vinith-suriyakumar](<https://devfeed.tech/tags/vinith-suriyakumar.md>)

### AI overview

MIT researchers and Thorn developed an auditing technique that assesses whether a generative AI model has been specialized to produce child sexual abuse material without generating illegal outputs. In testing, the procedure identified specialized model variants with 100 percent accuracy.

### Source excerpt

Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.