Understandably so, the buzz surrounding artificial intelligence (AI) is about how it can augment human intelligence and increase efficiency and production. Indeed, of all technologies developed in the past century, AI has the most power to enhance human thought processes and transform the way we do business. But to harness the full power of AI, we should use it for more than simply making work easier and more profitable. I believe it’s a moral imperative that we also use the incredible power of AI to advance the public good.

AI = new—and better—jobs

With the deployment of AI technologies, many tasks that drain worker efficiency will be automated. Automation won’t necessarily replace workers, however. Instead, it will give them freedom to concentrate on developing solutions to mission-critical problems they face instead of being bogged down in manual data analysis.

Also, AI implementations don’t just spring up, de novo, fully realized and optimized. There must be people who create the algorithms that form the backbone for AI. Workers will also be needed to “train” the AI systems to “think” like humans. Sure, AI can learn, but it needs a place to start, and it needs refinement via human input. Finally, there will be a great need for workers to serve as liaisons or interpreters between AI and the business people who use it. Of course, this will require re-thinking the way we educate our workforce of the future. But if we want the benefits of AI badly enough, we can–and must–figure out how to do that.

AI = better healthcare

Healthcare is the perfect vehicle to use AI for the public good. Cancer researchers are now using deep learning to create algorithms that analyze and categorize cancer biopsies faster, and more accurately, than humans. This process gives healthcare providers more and better information with which to make accurate diagnoses and plan treatments that extend lives.

AI is more than a futuristic set of science experiments. AI = better #jobs, improved #healthcare and potential solutions to the world's largest issues

Researchers are also compiling data on patient populations and combining that data with genomic data to develop personalized therapies for diseases such as cancer and drug addiction. With these personalized therapies, cancer care teams can develop targeted treatment programs that are more powerful and have fewer side effects. Drug addiction specialists can zero in on which physiological systems and psychological processes are most affected by a patient’s addiction. They can then more precisely target both medical treatments and psychological interventions to the patient’s needs.

AI = A shot at solving the worst global problems

According to the most recent estimates by the World Bank, in 2013, 10.7 percent of the world’s population lived on less than $1.90 US per day. That’s an estimated 1.1 billion people living in extreme poverty. AI can help change that. For example, researchers are deploying sophisticated imaging to examine where activities—say consumption of electricity—take place.

Researchers then couple this data with economic data to paint a picture of global poverty. With this data in hand, they can use AI to analyze why the poverty exists and predict whether it will spread. And—most importantly—they can use the data to create customized governmental and non-governmental policies and programs to alleviate and prevent poverty in the future.

The uses of AI that I’ve discussed here are only a few of the many, almost miraculous, uses of AI to advance society and make the world a better place. As technology advances, there is virtually no limit to the uses of AI. We can create smarter, more livable cities. We can lift people out of poverty and make them healthier. We can educate tomorrow’s generation to make the entire planet a better place to live—and to work. So, as we use AI to create amazing new ways to make money, we should also make sure that we’re using it to make our lives better as well.

Anu Jain
Anu Jain, Vice President, Americas, is at the forefront of the analytics, machine learning, and workflow orchestration revolution. Anu is a leader in Teradata’s transformation from a perpetual license model to a service organization that will drive innovation in open source, business solutions adoption, analytics, and workflow. He has deep technology and domain-specific thought-leadership and expertise in ad tech, media, front-office effectiveness, digital media and analytics-powered industry solutions. His expertise in technology-driven business transformation includes big data, cognitive analytics, predictive analytics, data mining, data warehousing, and business intelligence. Before coming to Teradata, Anu worked for IBM and Deloitte Consulting.

Anu also frequently blogs on his personal site: https://thinking-analytics.com/
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