THE AI INTERVIEW

lice Xiang did not necessarily set out to become one of the technology sector’ s leading voices on AI ethics. Instead, her path began with statistics and economics, studying both subjects at Harvard University. She completed a Bachelor’ s and Master’ s degree, before earning a further Master’ s in economics from the University of Oxford.

However, early on, Alice’ s primary interest was in applying empirical methods to human-centric data. This drew her naturally towards machine learning, a branch of AI in which systems learn patterns from data rather than following explicit instructions.

Working on early ML models, Alice noticed something troubling: few practical frameworks existed for evaluating bias in AI systems.

“ Early in my career, I worked on developing machine learning models and quickly saw the lack of standards or guardrails around bias in AI systems,” she reflects.“ That realisation made me want to focus on building more responsible technology.”

Today, Alice holds two senior roles at Sony, the Japanese conglomerate known for its electronics, entertainment and gaming businesses, alongside its growing AI research division, Sony AI.

As Global Head of AI Governance at Sony Group, she oversees the policies and frameworks guiding AI use across the company’ s many business units worldwide. Meanwhile, as Lead Research Scientist at Sony AI, she leads

TITLE: GLOBAL HEAD OF AI GOVERNANCE

COMPANY: SONY INDUSTRY: ELECTRONICS

Alice oversees the team shaping AI governance policies and frameworks across Sony Group’ s business units worldwide. In addition, she serves as Lead Research Scientist at Sony AI.

a team focused on responsible AI for creative industries and the protection of creator rights.

Sony AI was established in 2020 to accelerate fundamental AI research and development while supporting human imagination and creativity. Ethics has been central to that mission from the outset. Alice’ s research concentrates specifically on the quality and fairness of the data used to train AI models.

Why data matters more than outputs Public debate around AI ethics often focuses on what a system produces – whether that is a chatbot’ s response or the output from an image generator. Output, Alice argues, misses where the real problems begin.

“ AI outputs are the most visible part of the system,” she explains.“ When something goes wrong, it is the output that users experience directly, so scrutiny naturally begins there.”

20 July 2026