
The Markkula Center for Applied Ethics empowers people and organizations to make better decisions for a more caring world. The Journalism and Media Ethics program's aim is to help stakeholders across various news media occupations tackle complex ethical dilemmas in storytelling and AI-based digital distribution.
Traditional journalism ethics - premised on an older set of industrial and hegemonic norms of objectivity, neutrality and credentials-based sourcing - is allowing anti-democratic politics to manipulate discourse, instead of serving the cause of accuracy and truth-determination vital to democracies.
There is a movement underway to redefine professional journalism and its ethics. Our program works to clarify and elevate the ethical values of this movement and provide scholarship, tools and validation to support its growth amongst media practitioners.
Journalistic sourcing ethics and news distribution technology (search, social, aggregator, and AI apps) are operating like ships in the night. There is a new portal of opportunities for news distribution technology to incorporate knowledge of ethical sourcing to do justice to authentic and long-tail news stories in feed building and recommendations.
We help outline and defend the need for research and practical tools to pursue these opportunities at the news supply chain level - suppliers (stories) and distributors. A re-imagined supply chain could open up an otherwise competitive marketplace for news apps and non-traditional news publishers, and incentivize ethical journalism that fosters democratic culture.
The program offers trainings and workshops for news industry stakeholders; internships and fellowships for Santa Clara University students; interdisciplinary research collaborations with computer science and engineering, psychology and communications departments; scholarship in academic journals on media ethics.
Target Issues
One time bulk audits for sourcing and source diversity metrics in news stories from newsrooms or a WordPress based plugin system for semi-automated source reviews inside the CMS.
Target Issues