Brian Brackeen

Why organisations work with Brian Brackeen

• He has run a face recognition company at commercial scale and publicly refused to sell that technology to law enforcement, which gives his arguments on AI governance a credibility most consultants cannot match.
• He can speak to algorithmic bias from inside the engineering stack, not from the outside as a critic, because he has shipped the models and seen where the failure modes sit.
• As General Partner of a $50M fund backing underrepresented founders, he brings a capital-allocation lens to questions of inclusion that boards typically hear framed only as workforce or culture issues.
• His 2018 TechCrunch op-ed against police use of facial recognition shaped industry debate ahead of formal regulation. Boards weighing AI policy get a practitioner who set a market precedent, not a commentator describing one.

Biography highlights

• Founder and former CEO of Kairos, a face recognition AI company named to the Wall Street Journal’s Top 25 Startups list in 2013.
• General Partner at Lightship Capital, a $50M Cincinnati-based venture fund backing women, founders of colour, LGBTQ+ founders, and founders with disabilities.
• Author of a June 2018 TechCrunch op-ed arguing that commercial facial recognition should not be sold to government or police use.
• Returned to Kairos in 2021 as chair of the scientific advisory board, focused on eliminating racial bias in face recognition datasets.
• Earlier career: Senior Project Manager at Apple and Senior Managing Consultant at IBM.
• Co-founder of Lightship Foundation, which owns Black Tech Week.

Biography

Face recognition is one of the few AI categories where a founder has publicly walked away from a commercial market on principle. In June 2018, the CEO of Kairos published an op-ed in TechCrunch refusing to sell the company’s technology to law enforcement, citing the accuracy gap for people of colour and the consequences of misidentification. The argument landed before the broader regulatory conversation caught up.

That founder is Brian Brackeen. He had built Kairos from 2012, with prior operating roles at Apple as a Senior Project Manager and at IBM as a Senior Managing Consultant. Under his leadership, Kairos was named to the Wall Street Journal’s Top 25 Startups list in 2013 and positioned alongside Microsoft and Face++ in the global face recognition market. A board dispute removed him as CEO in 2018; he returned in 2021 to chair the scientific advisory board, with a specific mandate on algorithmic bias.

The work since has been about capital, not code. As General Partner at Lightship Capital, a $50M fund he runs with co-founder Candice Matthews Brackeen, Brackeen invests in underrepresented founders and in regions outside the coastal venture hubs. Lightship Foundation, the family’s parallel non-profit, owns Black Tech Week. The investing thesis treats inclusion as a market inefficiency, not a values exercise.

For senior leaders, the value of his perspective is the combination of these two operating experiences. He can describe where bias enters an AI system at the dataset level, why a vendor might be the wrong place to outsource that judgement, and what the capital signal looks like when an entire founder population is being underwritten by the same narrow set of pattern-matching investors.

Key speaking topics

• AI ethics and algorithmic bias
• Facial recognition and surveillance technology
• Responsible AI governance
• Venture capital and underrepresented founders
• Diversity in technology
• Entrepreneurship and scale-up leadership

Ideal for

• Boards and executive teams setting AI governance policy
• CTOs, CDOs, and Chief AI Officers responsible for deployment decisions
• Investors, LPs, and corporate venture teams reviewing portfolio inclusion
• Innovation and DEI leaders working at the intersection of product and people

Audience outcomes

• A practitioner’s account of where bias actually enters AI systems, and why surface-level audits miss it
• A defensible framework for deciding which AI use cases an organisation should refuse, not just constrain
• A clearer view of how capital allocation patterns shape which technologies get built and by whom
• Direct exposure to the trade-offs faced by founders deploying AI in regulated and sensitive contexts