Tag: Artificial Intelligence

When AI Turns Miscarriage into Murder: The Alarming Criminalization of Pregnancy in the Digital Age

The Petrie-Flom Center Staff Leave a comment

by Abeer Malik

Imagine: Overjoyed at your pregnancy, you eagerly track every milestone, logging daily habits and symptoms into a pregnancy app. Then tragedy strikes—a miscarriage. Amidst your grief, authorities knock at your door. They’ve been monitoring your digital data and now question your behavior during pregnancy, possibly building a case against you using your own information as evidence.

This dystopian scenario edges closer to reality as artificial intelligence (AI) becomes more embedded in reproductive health care. In a post-Dobbs world where strict fetal personhood laws are gaining traction, AI’s predictive insight into miscarriage or stillbirth are at risk of becoming tools of surveillance, casting suspicion on women who suffer natural pregnancy losses.

The criminalization of pregnancy outcomes is not new, but AI introduces a high-tech dimension to an already chilling trend. At stake is the privacy and the fundamental right of women to make decisions about their own bodies without fearing criminal prosecution. Alarmingly, the law is woefully unprepared for this technological intrusion.

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Health Care, AI, and the Law: An Emerging Regulatory Landscape in California

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by Rebekah Ninan

This past month, California Governor Gavin Newsom signed a wave of artificial intelligence-related legislation into law. Much public debate has been focused on SB 1047, a proposal ultimately vetoed by Governor Newsom, which would have held AI companies liable for “catastrophic harms” from AI models. Comparatively little attention has been paid to three new laws aimed at health care-related AI and data privacy. Three laws are AB-3030, SB-1223, and SB-1120. AB 3030 requires that health care providers disclose when they have used generative AI to create communications with patients. SB 1223 amended the California Consumer Privacy Act of 2018 to include neural data as sensitive personal information, whose collection and use companies can be directed to limit. Finally, SB 1120 limits the degree to which health insurers can use AI to determine medical necessity for member health care services. This article seeks to summarize these developments in the law.

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Q&A: Alex Zhavoronkov on Cognitive Enhancement, Anti-Aging, and AI Drug Development

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Interviewed by William Leonard Pickard

Alex Zhavoronkov, PhD, is Founder and CEO of Insilico Medicine, a leading clinical stage biotechnology company developing next-generation artificial intelligence and robotics platforms for drug discovery, with headquarters in Cambridge, MA and facilities around the world. He has invented critical technologies for the creation of novel molecular structures, and pioneered the prediction of human biological aging.

Q: Tell us about Insilico’s work

AZ: Insilico has two main focus areas: developing software and discovering and developing novel drugs for aging-related diseases (thus enhancement in neurodegenerative states and in healthy adults). When it comes to software, most of our platforms are commercially available for startups and academics with free trial access, and for some specific projects we can provide software for free in the form of a collaboration. When it comes to drug discovery, academics and startups can contact us to test our drugs in a variety of experimental models.

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Newspapers and Laptop.

AI, Copyright, and Open Science: Health Implications of the New York Times/OpenAI Lawsuit

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By Adithi Iyer

The legal world is atwitter with the developing artificial intelligence (“AI”) copyright cage match between The New York Times and OpenAI. The Times filed its complaint in Manhattan Federal District Court on December 27 accusing OpenAI of unlawfully using its (copyrighted and paywalled) articles to train ChatGPT. OpenAI, in turn, published a sharply-worded response on January 8, claiming that its incorporation of the material for training purposes squarely constitutes fair use. This follows ongoing suits by authors against OpenAI on similar grounds, but the titanic scale of the Times-OpenAI dispute and its application of these issues to media in federal litigation makes it one to watch. While much of the buzz around the case has centered on its intellectual property and First Amendment implications, there may be implications for the health and biotech industries. Here’s a rundown of the major legal questions at play and the health-related stakes for a future decision.

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President Joe Biden at desk in Oval Office.

What’s on the Horizon for Health and Biotech with the AI Executive Order

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By Adithi Iyer

Last month, President Biden signed an Executive Order mobilizing an all-hands-on-deck approach to the cross-sector regulation of artificial intelligence (AI). One such sector (mentioned, from my search, 33 times) is health/care. This is perhaps unsurprising— the health sector touches almost every other aspect of American life, and of course continues to intersect heavily with technological developments. AI is particularly paradigm-shifting here: the technology already advances existing capabilities in analytics, diagnostics, and treatment development exponentially. This Executive Order is, therefore, as important a development for health care practitioners and researchers as it is for legal experts. Here are some intriguing takeaways:  Read More

Silver Spring, MD, USA - June 25, 2022: The U.S. Department of Health and Human Services (HHS), U.S. Public Health Service (USPHS) and FDA logos are seen at the FDA headquarters, the White Oak Campus.

FDA Solicits Feedback on the Use of AI and Machine Learning in Drug Development

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By Matthew Chun

The U.S. Food and Drug Administration (FDA), in fulfilling its task of ensuring that drugs are safe and effective, has recently turned its attention to the growing use of artificial intelligence (AI) and machine learning (ML) in drug development. On May 10, FDA published a discussion paper on this topic and requested feedback “to enhance mutual learning and to establish a dialogue with FDA stakeholders” and to “help inform the regulatory landscape in this area.” In this blog post, I will summarize the main themes of the discussion paper, highlighting areas where FDA seems particularly concerned, and detailing how interested parties can engage with the agency on these issues.

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AI-generated image of robot doctor with surgical mask on.

Who’s Liable for Bad Medical Advice in the Age of ChatGPT?

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By Matthew Chun

By now, everyone’s heard of ChatGPT — an artificial intelligence (AI) system by OpenAI that has captivated the world with its ability to process and generate humanlike text in various domains. In the field of medicine, ChatGPT already has been reported to ace the U.S. medical licensing exam, diagnose illnesses, and even outshine human doctors on measures of perceived empathy, raising many questions about how AI will reshape health care as we know it.

But what happens when AI gets things wrong? What are the risks of using generative AI systems like ChatGPT in medical practice, and who is ultimately held responsible for patient harm? This blog post will examine the liability risks for health care providers and AI providers alike as ChatGPT and similar AI models increasingly are used for medical applications.

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Wooman doctor using tablet with creative glowing digital heart futuristic interface hologram. Medicine, cardiology and future concept.

The Council of Europe’s Artificial Intelligence Convention: Implications for Health and Patients

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By Hannah van Kolfschooten

The Council of Europe, the most important international human rights organization on the European continent, currently is drafting a Convention on Artificial Intelligence, Human Rights, Democracy and the Rule of Law (AI Convention). The Convention aims to protect fundamental rights against the harms of Artificial Intelligence (AI), and is expected to become a global leading convention, as non-European states such as the United States (U.S.) are considering becoming signatories.

As health care is one of the top industries for AI, the forthcoming AI Convention will have important implications for the protection of health and patients. This post gives a brief outline of the background, scope, and purpose of the AI Convention. It goes on to flag common human rights issues associated with medical AI and then touches upon the most important health rights implications of the current text of the AI Convention.

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Modern Medical Research Laboratory with Computer Showing Virus Genome Research Software. Scientific Laboratory Biotechnology Development Center Full of High-Tech Equipment.

How Artificial Intelligence is Revolutionizing Drug Discovery

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By Matthew Chun

In recent months, generative artificial intelligence (AI) has taken the world by storm. AI systems like ChatGPT and Stable Diffusion have captured the imagination of the masses with their impressive and sometimes controversial ability to generate human-like text and artwork. However, it may come as a surprise to some that — in addition to writing Twitter threads and dating app messages — AI is also well underway in revolutionizing the discovery of life-saving drugs.

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Medicine doctor and stethoscope in hand touching icon medical network connection with modern virtual screen interface, medical technology network concept

AI in Digital Health: Autonomy, Governance, and Privacy

The Petrie-Flom Center Staff Leave a comment

The following post is adapted from the edited volume AI in eHealth: Human Autonomy, Data Governance and Privacy in Healthcare.

By Marcelo Corrales Compagnucci and Mark Fenwick

The emergence of digital platforms and related technologies are transforming healthcare and creating new opportunities and challenges for all stakeholders in the medical space. Many of these developments are predicated on data and AI algorithms to prevent, diagnose, treat, and monitor sources of epidemic diseases, such as the ongoing pandemic and other pathogenic outbreaks. However, these opportunities and challenges often have a complex character involving multiple dimensions, and any mapping of this emerging ecosystem requires a greater degree of inter-disciplinary dialogue and more nuanced appreciation of the normative and cognitive complexity of these issues.

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