AI promises to expand healthcare delivery capabilities, but ethical safeguards must first be put in place.
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As artificial intelligence (AI) becomes an increasingly integral part of healthcare, the urgency of integrating ethical governance cannot be overstated.
Healthcare and healthtech companies must adopt a deep understanding of integrating accountability, ethics, and fairness into the AI lifecycle. We are on the threshold of a significant transformation in the application and impact of AI, requiring a balance between its benefits and a commitment to ethical development and use.
The advent of AI in healthcare will be a revolution: a true paradigm shift in patient care research, reducing the complexity of our healthcare system and increasing administrative efficiency. However, the rapid evolution of AI technologies is bringing complex ethical dilemmas to the forefront.
Commitment to Ethical AI
I lead an organization that aims to simplify the healthcare sector. As we serve many health plan clients, including nine of the top 10 payers, we are investing heavily in AI to reduce friction between health plans and providers, increase stakeholder savings, and reduce complexity for better understanding and greater consumer responsibility.
The role of AI in healthcare is multifaceted, delivering advancements in diagnostic accuracy, tailored treatment plans, improved financial experiences (for all stakeholders), and better outcomes for patients. Optimism surrounding AI’s impact on healthcare is considerable, reflecting its capabilities for data analysis, prediction and clinical support. However, alongside these opportunities, there is a crucial need to address the ethical implications of integrating AI into sensitive areas such as patient care and data management.
Understanding the ethical imperative
The trust gap in AI technologies in healthcare settings is significant. According to recent reports, more than 60% of patients do not trust AI in healthcare. This skepticism is rooted in concerns about data privacy, potential bias, and lack of transparency in AI decision-making processes. The ethical deployment of AI thus becomes not only a technical challenge but a moral and societal obligation.
In recent studies conducted by the Journal of Medical Internet Research and the Journal of Consumer Research, distrust of medical AI systems arises from concerns about the systems themselves and the practices of the companies developing these technologies. Respondents highlight concerns about data privacy, the challenges of collecting high-quality, accurate medical data, and the perception that tech companies value profit over human well-being.
As powerful as AI technology is, businesses must remember that it is human-to-human interactions, both in-person and digital, that are the essence of healthcare. AI in healthcare must prioritize human interactions, which requires a foundation of accountability and ethics in the creation, testing, deployment and monitoring of AI.
RAISE benchmarks: a strategic tool for AI security
In response to these challenges, the Responsible AI Institute introduced the RAISE repositories to facilitate the responsible development and deployment of AI.
These benchmarks, including the Corporate AI Policy Benchmark, the LLM Hallucinations Benchmark, and the Vendor Alignment Benchmark, are essential to guiding organizations toward compliance with global standards and addressing the challenges of generative AI and large language models.
- RAISE, reference in corporate AI policy. This tool assesses the scope and alignment of a company’s AI policies with the RAI Institute’s Enterprise AI Policy Model, which underpins the AI Risk Management Framework from NIST. It guides organizations in developing AI policies encompassing reliability and risk considerations specific to generative AI and LLMs.
- RAISE LLM Hallucinations Benchmark. This benchmark addresses the risk of AI hallucinations, a common problem in LLMs, which can lead to misleading results. It helps organizations assess and minimize these risks in AI-based products and solutions.
- Raise the supplier alignment benchmark. It assesses whether suppliers’ AI policies align with their customers’ ethical and responsible AI policies, ensuring seamless AI practice throughout the supply chain.
Deepen regulatory and policy frameworks
To harness the potential of AI ethically, healthcare leaders must navigate an evolving landscape of regulatory and policy frameworks. Initiatives like that of President Biden Executive Order on AIEuropean Union AI Act, Canadian Artificial Intelligence and Data Act and UK AI Safety Summit highlight growing global focus on developing safe and responsible AI .
Aligning with standards like the NIST AI Risk Management Framework and the upcoming ISO 42001 family of standards is crucial for healthcare organizations.
Building Trust Through Advanced Education and Engagement
Educating healthcare professionals and the public about the capabilities and limitations of AI is essential to building trust. This training should be comprehensive, address the benefits and challenges of AI, and educate patients about the impact of AI on their care.
The role of leadership in the ethical integration of AI
Senior business and technology leaders play a critical role in guiding their organizations toward ethical AI practices. Leadership commitment to AI ethical principles, transparent communication, and continuous evaluation of AI systems are essential to building a culture of trust and accountability.
While savings and business outcomes are of paramount importance, it is also important to think about what kind of defensible principles underpin usable solutions. Because AI is as powerful as it is today and will become, many regulatory agencies and consumer watchdog groups will keep a close eye on human controls, data protection, algorithmic/data biases, responsible design and monitoring, and impact at individual and systemic levels. .
AI in healthcare transcends technology; it’s a new era in patient care and efficiency. Leaders must guide their organizations toward ethically harnessing the potential of AI. The RAISE benchmarks provide a practical framework for this endeavor, balancing benefits, risk mitigation and building trust.
