AI Ethics & Responsible Technology speakers
Speakers who interrogate the human consequences of algorithmic decision-making, data ethics and emerging technology
Speakers Associates represents 149 speakers on AI Ethics & Responsible Technology, including Kemal Apaydin, Rahaf Harfoush, Limor Ziv, Harriet Farlow, Saakshar Duggal, Dr Sidney Shapiro, Tina Stowell, Timandra Harkness, Dame Wendy Hall and Susi O’Neill.
Boards now sponsor science they do not fully understand, in fields where the ethical questions arrive faster than the regulation. Genetics, fertility, biomedical data and synthetic biology now sit on corporate roadmaps and government policy desks, but most leaders cannot interrogate the underlying claims. The gap between the people building this technology and the people accountable for it is widening.
Boards now make decisions where the legal answer, the commercial answer, and the moral answer point in different directions. The default response is process: more codes, more training, more compliance. None of it changes how senior leaders actually decide under pressure, and none of it survives contact with a real ethical failure.
Boards are being asked to commit capital and credibility to AI before anyone has a settled view of what the technology will and will not do. The reflex is either to over-promise or to wait. Both positions are expensive, and neither produces the judgment a senior team needs to set policy on adoption, risk, and public trust.
When an AI system causes harm, most organisations cannot say who is accountable for it. Agentic AI sharpens the problem, because software now takes actions no one explicitly authorised. The legal and governance structures most companies rely on were built for tools that wait to be told what to do.
Organisations deploying AI in high-stakes decisions typically believe their governance frameworks are adequate. The evidence says otherwise: most widely used bias detection tools do not satisfy the legal standards they are meant to address, and explainability is frequently promised but rarely delivered in a form that holds up to regulatory scrutiny. Boards are making accountability commitments about AI that the technical systems underneath those commitments cannot actually keep.
Online abuse has moved from a personal hazard to a workplace one. Senior women, Black colleagues, and other targeted groups now carry a digital safety burden their employers do not see in the engagement survey. The unresolved question for people leaders is how to treat online harm as a duty of care rather than a personal coping problem, and how to do that in a corporate climate where inclusion language is under pressure.
Boards have committed to AI before they have decided what it is for. Pilots multiply, vendors crowd the agenda, and the gap between what the technology can do and what the organisation should do with it widens. Leaders need a credible read on which shifts matter, on what timeline, and which ones are noise.
Senior teams are not short of strategy. They are short of people who can keep moving when the information they are used to relying on goes dark. The hardest leadership question right now is how to make sound decisions, and rebuild composure across a team, when the usual signals stop arriving on time.
Most organisations have run AI pilots. Very few have converted them into operating performance. The gap is no longer about technical capability; it is about strategy, governance, sourcing decisions, and the readiness of the people who have to use the systems every day.
Most enterprise AI programmes are stuck between an executive mandate to deploy and an operating reality that cannot absorb the change. Boards want commercial returns. Workforces want to know what happens to them. Risk and compliance want to know how the model decides. The leaders running these programmes need someone who has actually shipped AI inside large companies, not someone describing the journey from outside.
Most AI investment is sitting between the slide deck and the operating model. Leaders have approved the strategy, but the people meant to use the tools are confused, sceptical, or quietly opting out. Closing that gap is a communications and adoption problem before it is a technology one, and very few organisations are treating it that way.