When the Best Medicine in the World Isn’t Enough, What Can Technology Do?
Technologists, healthcare providers, and patients must come together to address a community's health gaps.
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Big ideas, bold solutions. Explore the latest research, analysis, and policy insights from our experts.
Fifteen new universities and colleges join New America’s Public Interest Technology University Network
Announcing PIT-UN's new class of member institutions.
What We Learned In PIT-UN’s First Year
Lessons learned from a year of working with universities around the country to promote public interest technology.
What does it take for a public interest technology project to succeed?
Defining Public Interest Technology
What does it mean to apply technology expertise to the public interest?
Understanding Data Privacy Regulations
The new report from Harvard Kennedy School's TAPP project and PIT synthesizes key data privacy insights from over 40 diverse stakeholders.
$3.1 Million Awarded to Grow Field of Public Interest Technology at Leading Colleges and Universities
The Public Interest Technology University Network’s inaugural “Network Challenge” is awarding 27 grants to 21 colleges and universities.
The Ethical Character of Algorithms—and What It Means for Fairness, the Character of Decision-Making, and the Future of News
The ethical character of algorithms depends on the evaluation of the purposes for which they are designed and used.
The Need to Regulate AI Implementation in Public Assistance Programs
We must consider the possibilities for malintent that accompany the automation of agencies serving some of the population’s most vulnerable.
From Overconfidence in Research to Over Certainty in Policy Analysis: Can We Escape the Cycle of Hype and Disappointment?
The answer lies in understanding research methods and biases.
How to Fuel Government Innovation That Lasts
The answer lies in embracing innovation that's slow and small—instead of fast and flashy.
The Perfect Tweetstorm: Microsoft’s Tay and the Cultural Politics of Machine Learning
Machine learning algorithms are increasingly used in the lifestyle domain, quietly working in the background.