This blog has been in the works for a while—partly because it’s technical, and partly because I needed time to dig deeper into the subject. It’s also becoming increasingly relevant to the work we’re doing at HealthScoreAI™.
In our ongoing conversations about Artificial Intelligence (AI) in healthcare, we’ve made it clear: today’s AI isn’t ready to take the lead in diagnosing patients—at least not directly, and definitely not as the primary decision-maker. That said, AI has huge potential for consumers when they have access to all their health data.
Most venture capital–funded AI projects in healthcare are, frankly, “solutions looking for a problem.” It’s the biggest industry on Earth, and many of these projects will fail. Still, we’re confident that AI is already proving effective—and even life-saving—in fields like radiology, pathology, and genetics.
In this series, we’ll tackle what, for me, is the toughest of those areas: genetics. I promise it’ll be a worthwhile conversation.
A Groundbreaking Report
Late last year, the Ada Lovelace Institute (more on Ada—both the Institute and the historical figure—below) released a highly relevant 143-page report. Though only a few months old, it feels perfectly timed. We’ve been speaking with a range of organizations—universities, research labs, and data companies—who are gathering genetic data from patients and cancer cells in search of real solutions.
We’re deeply interested in this space, especially as we look to the future. We believe that combining a consumer’s own longitudinal data—acute and chronic medical history—with genetic insights and AI has the potential to change everything.
We’ve already seen this in action: from complex adult cases to rare pediatric conditions. The challenge is that a consumer’s data is spread across multiple systems. As a non-scientist, I’m fascinated by questions like: why do some people with “bad” genetic markers stay healthy, while others with clear warning signs face unpredictable diseases? Maybe the clues are hidden deep in an old medical file, or in a medication reaction, or some environmental exposure we haven’t yet understood. With access to enough clean clinical data, AI might actually be able to find those patterns.
One important report—Predicting the Future of Health: The Ethical Considerations and Societal Impact of Health AI Models—from the Ada Lovelace Institute offers some excellent insights, ideas, and suggestions. At 143 pages, it’s a deep dive, so I’ll summarize the most relevant parts over a series of upcoming blog posts.
Overview: Health Prediction AI
This report examines how health prediction models powered by AI are being used, what benefits they offer, and what ethical issues we need to be aware of. It focuses heavily on AI-Powered Genomic Health Prediction (AIGHP).
What is AIGHP?
Think of AIGHP as a sophisticated health fortune teller—not one reading tea leaves, but one reading your DNA.
It uses AI to analyze your genetic code and predict:
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Which diseases you’re likely to develop
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How well you might respond to specific medications
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What long-term health risks you may face
How It Works
Our DNA contains thousands of small variations—like those that determine your eye color or height. While each variation might have a small impact on its own, together they can paint a clearer picture of your health. This process is known as polygenic scoring—essentially creating a risk score based on many genetic factors.
To simplify: traditional disease prediction is like looking at a single cloud to predict rain. Polygenic scoring looks at the whole sky—clouds, wind, pressure, humidity—to give a much better forecast.
Current Applications of Health Prediction AI
The report highlights where health prediction AI is already in use—and where it’s headed:
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Clinical decision support: Helping doctors diagnose and choose treatments
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Resource planning: Predicting hospital admissions and patient flow
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Population health: Identifying high-risk groups for early intervention
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Drug development: Speeding up the discovery of new treatments
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Personalized medicine: Matching treatments to individual genetic profiles
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Disease surveillance: Tracking public health trends
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Mental health and chronic care: Predicting flare-ups and tailoring care plans
A Convergence Revolution
The report emphasizes that we’re at a revolutionary moment: the convergence of longitudinal health data, genomic insights, and advanced AI. Together, they promise a huge leap in how we understand and manage health.
This convergence could:
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Create lifelong health profiles to spot risks decades early
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Map complex disease risk with polygenic scoring
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Predict how people respond to medications with precision
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Identify causes of unexpected outcomes
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Shift medicine from reactive to truly preventive
With AI’s ability to integrate text, imaging, sensor, and genomic data, it can even detect patterns across time, suggest potential causes—not just correlations—and do it all while protecting privacy through federated learning.
Benefits & Opportunities
AI in healthcare offers serious upsides:
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Early interventions—spotting disease before symptoms show
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Better treatment matching—personalizing care
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Efficiency—avoiding unnecessary procedures
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Stronger system planning—anticipating health trends
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Empowered patients—with insights to guide their own health
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Advances in research—fueling discovery
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Precision public health—targeting the right groups at the right time
Challenges & Concerns
But there are real concerns too:
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Data quality—garbage in, garbage out
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Bias—models can reinforce health disparities
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Privacy—handling sensitive genetic data
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Transparency—how do these models make decisions?
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Equity & Access—who benefits and who gets left out?
There’s also the psychological side: how do people cope with long-term risk predictions? How do we avoid health forecasts becoming self-fulfilling prophecies?
Who Was Ada Lovelace?
From their website:
The Ada Lovelace Institute was established by the Nuffield Foundation in early 2018, in collaboration with the Alan Turing Institute, the Royal Society, the British Academy, the Royal Statistical Society, the Wellcome Trust, Luminate, techUK and the Nuffield Council on Bioethics.
We are funded by the Nuffield Foundation, an independent charitable trust with a mission to advance social wellbeing. The Foundation funds research that informs social policy, primarily in education, welfare and justice. In addition to the Ada Lovelace Institute, the Foundation is also the founder and co-funder of the Nuffield Council on Bioethics and the Nuffield Family Justice Observatory.
The Institute is named after Ada Lovelace, often considered the world’s first computer programmer. She was the daughter of Lord Byron and worked with Charles Babbage on early computing concepts in the 1800s.
My Fascination With Innovation
If you’re into innovation like I am, you’ve probably read Walter Isaacson’s The Innovators. I’ve read it three times. It’s an incredible book that traces 200 years of computing history, linking visionaries like Charles Babbage, Ada Lovelace, Alan Turing, Grace Hopper, Steve Jobs, and more.
Ada Lovelace stands out to me—not just for her role in computing history, but because the modern-day institute bearing her name is driving important conversations about the ethics and potential of AI.
Empowering the Consumer
Let me be clear: AI still isn’t ready to diagnose patients directly—not without help, and not without serious prompting from experts. I’m not saying that just as an observer; leading scientific papers back it up.
But AI is great at a few things today: imaging (from X-rays to MRIs), pathology, and genetics. And in the future, when AI can tap into a person’s full longitudinal health history, the impact could be massive.
If you add genetic data to diagnostic and clinical data and then apply AI? The value grows exponentially. That’s what we’re focused on.
In the next post, we’ll explore more of this remarkable report, what it recommends, and how our customers can use this information to improve their health. You won’t want to miss it.
About HealthScoreAI ™
Healthcare is at a tipping point, and HealthScoreAI (HSAI) is positioning to revolutionize the industry by giving Consumers control over their health data and unlocking its immense value. U.S. healthcare annual spending has exceeded $5 trillion with little improvement in outcomes. Despite advances, technology has failed to reduce costs or improve care. Meanwhile, 3,000 exabytes of Consumer health data remain trapped in fragmented USA system of 500 EHRs, leaving Consumers and doctors without a complete picture of care.
HealthScoreAI seeks to provide a unique solution, acting as a data surrogate for Consumers and offering an unbiased holistic view of their health. With over 850 million medical claims denied annually in the U.S., HSAI intends on giving Consumers practical tools to respond to denial of care by insurers. We aim to bridge the gaps in healthcare access and outcomes. By monetizing de-identified data, HealthScoreAI seeks to share revenue with Consumers, potentially creating a new $100 billion market value opportunity. With near-universal EHR adoption in the USA, and advances in technology, now is the perfect time to capitalize on the data available, practical use of AI and the empowering of Consumers, in particular the 13,000 tech savvy baby boomers turning 65 every single day and entering the Medicare system for the first time. Our team, with deep healthcare and tech expertise, holds U.S. patents and a proven track record of scaling companies and leading them to IPO.
Noel J. Guillama-Alvarez
https://www.linkedin.com/in/nguillama/
+1-561-904-9477, Ext 355
https://www.adalovelaceinstitute.org/Report/predicting-the-future-of-health/
https://www.themarginalian.org/2014/12/10/ada-lovelace-walter-isaacson-innovators/
https://en.wikipedia.org/wiki/Walter_Isaacson