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How A New Review Process Won the Wharton Hack-AI-thon, Presented by Expedia Group

Team WayWise poses after winning the 2026 Wharton Hack-AI-thon

Now in its third year, the Wharton Hack-AI-thon, presented by Expedia Group, brought together some of Penn’s most ambitious builders to tackle real-world challenges at the intersection of artificial intelligence and business. This year’s competition was no exception, marked by rapid prototyping, late-night debates, and a final round full of energy, precision, and creativity. Read More

Building AI Products That Last: Lessons from SXSW 2026

Headshot of a person in a suit against a blue, circular pattern background.

At a packed session at SXSW this spring, Wharton Human-AI Research (WHAIR) faculty co-director Kartik Hosanagar and Microsoft chief product officer Aparna Chennapragada offered a candid and complementary set of lessons for builders navigating the fast-moving AI landscape. Their shared thesis: in AI product development, competitive advantage is both harder and easier to achieve than most people assume.  Read More

Penn AI Month 2026

Text on a blue and purple gradient background reads 'AI Month at Penn' and 'Human-Centered AI' with abstract wave designs.

Throughout April, we’re joining the University of Pennsylvania in celebrating Penn AI Month — a month-long, University-wide initiative featuring panels, workshops, lectures, and community events focused on human-centered AI. Read More

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Knowledge at Wharton

Research and Insights

Judgment Is the New Bottleneck

Headshot of a person named Ritcha Ranjan featured on a poster for an event or collaboration by Expedia Group and Accenture.

Wharton’s Matthew Bidwell speaks with Ritcha Ranjan, senior vice president of product at Expedia Group, on why building effective AI systems means designing for human judgment.Read More

When AI Transparency Backfires

A person holding a magnifying glass focusing on the letters

New research shows that AI and machine learning models can be made to look fair and neutral in their interpretability outputs while continuing to produce biased real-world decisions.Read More