The feats achieved through AI and machine learning are astonishing and can feel like modern wizardry. But without clear ethical reasoning and principled leadership, this utopian promise could tumble all too quickly into a dystopian nightmare.
Succeeding in the digital economy requires reinventing the way companies work, starting with an AI-powered operating model. Harvard Business School Professors Marco Iansiti and Karim Lakhani introduce a framework for how business roles need to change for people and tech.
Companies are tapping machine learning and artificial intelligence to help in the fight. Jeff Wen, a PhD student at Stanford, shares how these powerful tools are navigating vast, complex data to improve decision making.
While travelers are sprinting to tight connecting flights, airports are scrambling to make predictions. Visiting Associate Professor Yael Grushka-Cockayne, alongside Heathrow Airport and researchers at University College London, recently built and demoed a machine learning model that removes the guesswork.
Is Tuesday actually the best time to book a flight? Emily Batt (MS/MBA '20), formerly senior product manager at KAYAK, debunks this urban myth and gives us a peek inside the company’s price prediction models.
Even a perfectly designed algorithm makes decisions based on inputs from an imperfect world. Harvard Magazine pulls back the curtain on how AI operates — outside a vacuum, in real life — and the ethical awareness needed so the world being built is one we actually want to live in.
Despite the number of high-stakes applications, Al doesn’t come with a warning label. The health-tech professionals behind this article recommend concepts and tools from clinical research to serve as a starting point in navigating the complicated territory that is AI regulation.
How do we use AI technologies to address bigger social issues? What new regulatory and governance models are needed? From our 2018 Future Assembly, Harvard Law School Professor Chris Bavitz starts the multidisciplinary conversation.
Diversity of thought isn’t a nice-to-have when it comes to tech and business; it’s a requirement. Our 2019 Digital Transformation Summit explored the ethics of AI and implications for business decision-makers — from the perspectives of a philosopher, general counsel, and CEO.
Technologists, managers, and policymakers all have a seat at the table here. Assembly, a collaboration of the Berkman Klein Center for Internet & Society at Harvard and the MIT Media Lab, is about creating space for cross-sector teams to crack the code to some of AI’s toughest ethical and governance problems — problems that would otherwise fall out of reach.
Fairness has always been something we've struggled with as a society. David Weinberger, a senior researcher at the Berkman Klein Center for Internet & Society at Harvard, unpacks why fairness is a problematic framing of the ethical issues machine learning forces us to confront.