Invisible but powerful algorithms underpin much of modern life—from powering vast online marketplaces to facilitating airport check-ins without requiring you to show your passport. By cutting through the online clutter to bring tailored information and propose decisions based on data, algorithms can personalize recommendations and actions to match our tastes and personal attributes. They are designed to improve outcomes for all of us, save us time, and along the way, improve the efficiency and profitability of the service providers.
Earlier on, algorithms would be curated collections of rules or instructions that govern how a task is to be conducted, step-by-step, to reach a rule-based decision to achieve a desired result.
Today, with a boom in artificial intelligence underway, algorithms are doing much more than following preset instructions. Thanks to the development of machine learning, algorithms can now process troves of data and learn on their own without being explicitly programmed, gradually improving their accuracy as they gather and process more data.
Data is an asset, and it is doubling globally every year. Companies all over the world are capturing and storing as much data as they can, understanding not only that data plays a crucial role in leveraging the AI algorithms of today, but also that data is an essential ingredient to achieving innovation and growth. A case in point is a retailer using location sensors to improve the efficiency of shipments, or processing data from wearables to help workers avoid workplace injuries.
But with great power comes great responsibility. Algorithms are raising questions about data use and data privacy, and their structure—from how they are estimated to how they are used— can absorb the biases found in larger society and then reinforce it, deepening inequalities. And with the recent explosion of AI, it will be increasingly important for us to consider the potential ramifications of super-intelligent machines and determine how best to use them. The potential for unintended consequences shouldn’t preclude us from wielding this powerful technology. But it does require that we identify and responsibly manage how algorithms are deployed to ensure outcomes are fair, perhaps leaning on a bit of human intervention and adding some reasonable guardrails.
Fortunately, while algorithms may be hidden from public view, practitioners, regulators, academics—including Columbia Business School faculty—and others are addressing these questions, with the aim to improve outcomes, mitigate risk, and increase transparency.
With many ethical questions still unanswered, much work remains to be done. The next generation of business leaders will need the skills and judgment to realize the full potential of these technologies and wisely manage their influence and impact.
While algorithms can help save lives and quickly solve complex problems, it’s our collective responsibility to keep an eye on the way they are programmed and trained to make suggestions and drive decisions.