Dr. Patrizia Ariane Ecker

Patrizia Ecker is a postdoctoral researcher at the Lab of Ethics of AI and Neuroscience (Prof. Marcello Ienca). She holds a PhD in the psychology of digital media, with doctoral research on confirmation bias and belief formation in online environments - work published as a monograph with Palgrave Macmillan/Springer Nature under the title The Digital Reinforcement of Bias and Belief.

Before joining TUM, Dr. Patrizia Ecker spent more than fifteen years in management consulting, where she led large-scale AI and digital transformation programmes for Fortune 500 and DAX 30 organisations, including group-wide AI transformation, governance and change-management mandates in the financial sector. This combination of empirical research on human decision-making and hands-on experience with organisational technology adoption informs her current work on how ethical requirements can be embedded in the practice of technology development rather than applied to it retrospectively.

Research Areas

Her work sits at the intersection of applied ethics, the psychology of technology adoption, and the governance of emerging technologies. Key interests include:

• Embedded ethics in AI and neurotechnology development
• Responsibility and legitimacy in emerging technology governance
• Cognitive and confirmation bias in digital environments
• Governance of neural data (EU AI Act, neurorights)
• AI literacy and human-centred AI adoption

Professional Activities

She works on the NeuroTranslate project, which investigates embedded ethics for trustworthy and fair AI-based neural decoding, contributing to Focus Area 4 (Responsibility and Legitimacy) of the TransforM cluster, and contributes to the ethics and data-governance work package of the NEO project. She is the founder of the AI Literacy Alliance, a non-profit initiative promoting AI literacy in education and civil society, and speaks internationally on AI, technology psychology and digital transformation, such as the Web Summit.

• Embedded ethics in AI and neurotechnology development
• Responsibility and legitimacy in emerging technology governance
• Cognitive and confirmation bias in digital environments
• Governance of neural data (EU AI Act, neurorights)

• AI literacy and human-centred AI adoption