Ethical Considerations in Policy Advising

Too many examples of healthcare organizations ignoring ethics for innovation are popping up. Risking negative implications on patients. The ones healthcare is here to support. Numbers from a recent WHO report show that many countries lack ethical guidelines and risk assessments for AI in healthcare (https://lnkd.in/e7-fKYEr). Studies have shown that hospitals are not validating models locally before deployment (https://lnkd.in/eD4dJccf). Risking bias Reducing health equity Risking patient safety Digital health technologies also don't meet the minimum clinical safety and legal requirements (https://lnkd.in/eHcQhkMe). Meaning that healthcare organizations are implementing tools without confirming whether they are safe to use. Again, impacting patient risks. These are not isolated cases. They are a trend. Where ethics is taking the backseat. In the race for innovative solutions, it's essential to be aware of the ethical dilemmas that could undermine our progress. So, how do we make sure ethical deployment of AI? Here are 6 key aspects to get you going. 1️⃣ Start Ethical: Integrate ethical considerations from day one, prioritizing data security, patient well-being and ethical standards. 2️⃣ Bias Awareness: Understand and address data and algorithmic biases to prevent skewed outcomes and safeguard patient care. 3️⃣ Guidelines for Ethical Data: Establish clear guidelines for ethical data collection, conducting regular audits to maintain integrity. 4️⃣ Transparency Matters: Ensure transparency and explainability of tools to build trust among stakeholders and encourage accountability. 5️⃣ Diverse Teams: Build diverse and ethically aware AI development teams to mitigate oversight in ethical decision-making. Include stakeholders such as: Patients Clinical staff Administrative staff Technology providers Organizational leadership AI solutions developers and data leads 6️⃣ Identify and Mitigate Risk Identify and evaluate risks, such as potential adverse events. Are the risks proportionate to the benefits? Involve strategies to mitigate the potential risks. 7️⃣ Continuous Monitoring: Regularly monitor for stability, output consistency, and ongoing performance. Making sure that no patient groups will be negatively impacted. I don't want to live in a world where ignore risk detection for patients is the norm. Yes, sometimes the positive impact outshines the risk. But that does not make it okay to ignore the potential risks. What are you doing to ensure ethical deployment of AI in your organization?

Rapid advancements in neuroS/T pose significant ethical challenges that demand robust policy frameworks. Toward such, John Shook and I have proposed 6 precepts that we believe provide a comprehensive foundation for such policy, and which enable neuroscientific progress to align with societal values and human rights. These are: 1. Protecting Autonomy and Liberties of Persons: Policies must ensure that assessments and interventions (ie.- therapeutic or enhancing) are consensual and respect the integrity of individuals. This is particularly critical in contexts wherein lines between voluntariness and coercion can blur. 2. Promoting Public Health and General Welfare: Public health initiatives that leverage neuroscience must seek to maximize communal well-being without infringing on personal freedoms. 3. Prioritizing Ethically Sound and Economical Distribution of NeuroS/T Resources: Equitable access is essential to prevent exacerbation of social inequalities. Economic considerations should guide resource allocation without compromising ethical standards. 4. Preventing Neglect of the Vulnerable: Policies should implement safeguards to prioritize the rights and needs of these groups, so that they are not marginalized in pursuit of scientific progress. 5. Preserving the Constitutional Legality of the Justice System: NeuroS/T increasingly intersects with the legal system, from assessments of criminal responsibility to the looming potential of “neuro-correctives”. Policies must uphold constitutional principles such that neuroscientific evidence, methods, and tools are used judiciously and do not undermine legal rights or due process. 6. Publicizing Sound Science for Public and Political Understanding: Effective communication of neuroS/T developments is crucial for informed public discourse and, reciprocally, for policy-making. Transparency and clarity in scientific findings can prevent misinformation and foster a well-informed polis – and political system. Policies should support research, educational, and use initiatives, and foster open dialogue between scientists, policymakers, and the public. We propose that these precepts provide a starting point, which progresses from ethically informed discourse – and dialectic – to enable support for navigating the complex landscape of neuroS/T on the contemporary social stage. #neuroS/T #neuroethics #policy #brain science #Bioethics and Brains

What do students at IE Law School worry about most when we discuss ethics, policy, and technology today? After reviewing a large number of student reflections in an Ethics & Values course, a clear message emerges, one that in my opinion could matter to policymakers, regulators, universities, and employers alike. Key concerns students repeatedly raise: . Relativism: the fear that if “everything is just culture or opinion,” it becomes impossible to criticise injustice or protect fundamental rights. . AI and automated decision-making: especially in hiring, surveillance, and data use — students are acutely aware that bias is being scaled, not eliminated. . Egoism in systems and leadership: incentives that reward self-interest over responsibility, solidarity, and long-term societal impact. . Erosion of shared truth: in a digital environment shaped by AI-generated content, misinformation, and competing realities. What they value and explicitly ask for: .Clear ethical frameworks that translate values into enforceable norms (e.g. EU anti-discrimination law, GDPR). .Applied ethics, not abstract moralising: real cases from policy, business, technology, and governance. .Inclusive decision-making models (such as Deep Democracy), paired with clarity about ethical limits. .Spaces for structured, respectful disagreement, especially across cultures and disciplines. What is striking is this: Students are not asking for comfort or easy answers. They are asking for criteria, accountability, and ethical boundaries in a complex, globalised, and tech-driven world. Call to action: .To policymakers: ethics must be embedded early and not retrofitted after harm occurs. .To universities: ethical reasoning is not “soft skills”; it is core governance competence. .To employers: future professionals expect clarity, fairness, and responsibility, especially where AI and data are involved. If we want ethical resilience in our institutions, we need to take these concerns seriously — now, not later. Photo Credit: Julia Robles at an event by Mujeres Avenir and not related to IE Law School.

We often discuss policy outcomes without reflecting on the policy maker... We debate instruments. We analyse impact. We model trade-offs. But we rarely pause to examine the most decisive variable in public policy: The human being who makes the decision. Policy is not an algorithm. It is not an optimisation problem solved by an AI system. It is a profoundly human act. Behind every policy choice stands a person, or a group of persons, carrying: Cognitive biases Ideological commitments Moral intuitions Political incentives Career anxieties Incomplete information Bounded rationality (as Herbert Simon reminded us) Policy is not merely about evidence. It is about judgement under uncertainty. In an era of big data and predictive analytics, we are tempted to believe that better datasets automatically produce better policies. They do not. But better judgement does. And good judgement is not accidental. It is cultivated. It rests on three foundations: 1. Judgement The capacity to make decisions in ethically complex, value-laden, ambiguous situations; where no spreadsheet can give the final answer. 2. Openness Intellectual humility. The courage to say, “I may be wrong.” The willingness to listen across ideological divides. The discipline to update one’s beliefs when evidence shifts. 3. Compassion A deep concern for human dignity. An instinct to ask: Who bears the hidden cost? A commitment to long-term well-being over short-term optics. A technically brilliant but compassion-deficient policy maker can cause immense harm. A morally sincere but intellectually closed policy maker can do the same. Policy making is therefore not simply a technical function. It is a test of compassion and long term view of human flourishing. If we want better public policy, we must invest not only in better frameworks and analytics, but in developing better policy makers. Education systems, civil service training, and leadership development must emphasise: Ethical reasoning Bias awareness Cross-disciplinary literacy Empathy Deliberative dialogue Because policies rarely fail due to poor drafting. They fail because they are conceived narrowly. And narrowness is a human limitation. In AI, “Attention Is All You Need” reshaped computation. In governance, the deeper truth may be this: Judgement, Openness, and Compassion are what we need! Thapar Institute of Engineering & Technology #PublicPolicy #Governance #Leadership #Judgement #Compassion #EthicalLeadership