Imagine receiving a video of yourself committing a crime. You know it’s fake, but it looks so real that your friends, employer, or even law enforcement might not believe you.
This isn’t science fiction—it’s the unsettling reality of deepfake technology, a rapidly evolving form of artificial intelligence (AI) that creates hyper-realistic but entirely false audio, video, or images.
AI is reshaping industries at an unprecedented pace, promising transformative innovations while introducing complex risks.
In healthcare technology, these risks extend beyond theoretical concerns—they directly impact patient care, privacy, and trust. Yet, the public policy landscape is lagging behind AI’s growth, leaving consumers vulnerable to scams and exploitation.
With AI technology being used in every industry, from healthcare to finance, its potential for both good and harm grows exponentially.
Key Takeaways
AI technology is transforming healthcare, but its rapid growth demands equally rapid regulation to address risks and ensure patient safety.
- Deepfake technology and biased AI systems pose significant risks to patient care, privacy, and trust in the healthcare industry.
- Stronger federal laws are needed to protect patient data from hacks, breaches, and unconsented sharing, as well as to address bias in training datasets.
- Federal leadership is essential for establishing global benchmarks and ensuring accountability, transparency, and fairness in AI development and deployment.
Artificial intelligence in health tech
Artificial intelligence is transforming healthcare in unprecedented ways, offering innovative solutions that are reshaping the medical field and improving patient outcomes.
Advanced algorithms now enable faster diagnoses by analyzing X-rays, MRIs, and other medical scans with unmatched precision, allowing for earlier detection of diseases and more accurate results.
In addition, AI has made precision medicine a reality, creating personalized treatment plans tailored to a patient’s unique genetic makeup and lifestyle data. This ability to process massive amounts of information means doctors can deliver more targeted and effective care.
AI is also revolutionizing drug discovery, significantly accelerating the development of new treatments and reducing the time it takes to bring life-saving medications to market.
While these advancements hold tremendous promise, the growing reliance on AI also exposes healthcare systems to new and unprecedented vulnerabilities.
Issues surrounding privacy, trust, equity, and accountability must be addressed to ensure that the benefits of AI do not come at the expense of patient safety or fairness.
The privacy problem
One of the most pressing concerns is data privacy. Healthcare AI systems depend on enormous amounts of sensitive patient data to function effectively. But where does that data go? Who owns it? And what happens if it’s misused?
While regulations like the EU’s General Data Protection Regulation (GDPR) and initiatives like the U.S. Genetic Information Nondiscrimination Act (GINA) offer partial protection, gaps remain.
Many health apps and wearable devices, for example, operate outside the safeguards of HIPAA (the Health Insurance Portability and Accountability Act). This lack of oversight leaves patient data vulnerable to hacks and breaches as well as unconsented sharing.
Social networks and genetic testing companies often profit from sharing user data without clear patient consent. Sensitive medical records can also be stolen, sold, or exploited.
Stronger federal laws are needed to ensure transparency, ownership, and security when it comes to personal health information.
Bias in AI: Unequal healthcare outcomes
Another significant risk is bias in training datasets, which can have potential impacts on patient outcomes. Diagnostic tools and predictive models rely on vast datasets for training.
If these datasets are incomplete, unrepresentative, or biased, the resulting AI models can produce harmful errors. For example, some AI systems have shown:
Underdiagnosis in minority groups: Algorithms trained primarily on data from white patients may misdiagnose underrepresented populations, perpetuating healthcare inequities.
Discriminatory outcomes: Predictive tools may overlook critical warning signs for certain demographics, reinforcing systemic inequalities.
Bias in AI doesn’t happen intentionally, but it highlights a critical need for oversight. Policymakers must ensure that healthcare AI tools are rigorously tested for fairness and inclusivity before deployment.
The cost of inaction: Scams, deepfakes, and fraud
As AI tools become more affordable and advanced, the opportunities for misuse grow exponentially. In healthcare, this includes:
AI-Powered Scams: Fraudulent telehealth services or fake health apps are deceiving consumers, often collecting and exploiting sensitive data.
Deepfake Exploitation: Hyper-realistic AI-generated content, like fake videos or audio, can be used maliciously in insurance fraud, identity theft, or misinformation campaigns.
Alyssa Rosa, a victim, testified about her experience with AI-generated pornography—a chilling example of the emotional and social harms these technologies can cause. The ease of creating deepfakes today highlights the urgent need for regulatory action.
Without stronger federal oversight, consumers remain vulnerable to exploitation, with devastating financial and emotional consequences.
Why patchwork solutions fall short
Some states, like Colorado, are stepping up to address AI risks. Governor Jared Polis recently signed Senate Bill 205, which targets bias in AI development.
Colorado Attorney General Phil Weiser emphasized the importance of this legislation, even while acknowledging that state-level efforts are “second best” compared to a comprehensive federal approach.
The problem with a patchwork of state regulations is twofold: inconsistency and global leadership. Varying laws across states create confusion, open loopholes, and leave consumers in some regions less protected than others.
Additionally, without unified national standards, the U.S. risks losing its competitive edge and falling behind countries like China, which are aggressively pushing for global influence over AI governance.
Senator John Hickenlooper has been vocal about the need for federal leadership. “Great legislation starts with its first hearing,” he said during a Senate session, stressing the urgency of creating national AI standards.
Hickenlooper’s TAKE IT DOWN Act is one example of proposed legislation aiming to protect children from AI-generated exploitation. But experts warn that fragmented efforts won’t be enough. To address AI’s growing risks, a unified, proactive approach is essential.
Why federal leadership is essential
Federal leadership in AI regulation isn’t just about setting rules—it’s about establishing a global benchmark.
The U.S. risks losing its position as a leader in shaping AI governance without unified national standards. This opens the door for other nations, like China, to dominate the conversation and set policies that may not align with American values or priorities.
To address this challenge, federal regulation must tackle several critical areas. First, it must ensure data privacy and ownership by creating clear rules that protect patient data and promote transparency around how it is collected, shared, and used.
Second, regulations must address bias and fairness by implementing rigorous testing requirements for AI systems to identify and mitigate discriminatory outcomes.
Finally, there must be a focus on accountability, defining clear lines of responsibility for errors, failures, or misuse of AI technology to safeguard consumers and ensure trust.
At the same time, international collaboration is essential. As AI continues to evolve globally, countries must work together to create harmonized standards that strike a balance between fostering innovation and protecting consumers.
Without such cooperation, inconsistencies in regulations across borders could create loopholes, further exacerbating the risks posed by unregulated AI.
Empathy: The human element AI can’t replace
While AI can enhance healthcare, it cannot replicate the human touch—empathy, compassion, and understanding that are critical in patient care. In fields like psychiatry, pediatrics, and obstetrics, trust and emotional connection are essential.
No matter how advanced AI becomes, robotic systems lack the ability to provide comfort during a difficult diagnosis or share joy during a positive outcome. Policymakers must ensure that AI serves as a tool to enhance human-centered care, not replace it.
The path forward
AI holds immense promise for the healthcare industry, but its rapid growth demands equally rapid regulation. Without strong, unified federal leadership, we risk leaving patients vulnerable to bias, fraud, privacy breaches, and emotional harm.
Senator Hickenlooper and other advocates have made it clear: the time to act is now. Effective regulation must prioritize data privacy, accountability, and fairness while promoting innovation.
If policymakers fail to act, the cost of inaction will only grow. As AI technology becomes more powerful, its misuse will become more dangerous. It’s time for the U.S. to step up, set global standards, and ensure that AI enhances healthcare without compromising trust, equity, or safety.
By addressing these challenges today, we can harness AI’s potential to improve patient care—while protecting the people it’s meant to serve.
