Presented by Deloitte Consulting LLP
So, you know about the benefits of AI for business — how it can reduce time spent on manual tasks, improve data-driven decision-making, and allow humans to focus on strategic business initiatives. But have you considered AI for social impact?
Initiatives like IBM’s Science for Social Good, in which the company partnered with 19 NGO and government agencies, are accelerating the pace of problem-solving to improve global challenges and positively impact human livelihood, while positively influencing business.
The cost of computation and the volume of inputs required to solve vast problems using this powerful technology is more affordable and practical than ever before. “AI for good” is becoming an increasingly strategic priority for business and the public sector — which need each other (and technology) to solve the world’s most complex problems.
“We’ve finally reached an inflection point — we’re seeing a horizon where we can make positive changes for society by leveraging AI,” says Hemang Dholakia, managing director, Deloitte Consulting LLP. “We can tackle some genuinely impactful issues using AI and machine learning, especially when coupled with IOT or blockchain.”
Dholakia is particularly passionate about the following three examples, which are just a few of the applications that companies across industries and public agencies are exploring together
Increasing water access and resource management
Water access and resource management is a major crisis in developing countries — and the fundamental issue is about financing these resources. Using AI, years of data can be gathered from various climate satellites (which belong to the U.S. and/or other countries). This data can help determine where rainwater accumulation and runoffs happen, more accurately predict drought cycles, and find higher-yield water sites.
In more developed or urban areas, aging public utility infrastructures are beginning to break down, causing health and safety concerns for citizens. Scientists and technologists are determining how AI and IOT sensors can monitor public utility networks and help governments build data-driven maintenance cycles. In this way, the limited resources available in public waterworks systems can be maximized through AI-enabled preventive repair and maintenance.
“Ultimately, the most important part of this is leveraging resources in a sustainable manner,” Dholakia explains. “Looking ahead, AI can enable us to better study climate, human activity, and industrial usage patterns so public utility companies can better serve citizens, and developing countries can plan and build resource networks more efficiently.”
Using data insights to help tackle addiction
It’s both a social and an economic crisis: Every day, more than 130 people die from an opioid overdose, and every year the U.S. spends $78.5 billion trying to stem the tide.
“Potential new approaches to addressing the opioid crisis are showing real promise,” Dholakia says. “AI is being used to learn about what increases the odds of addiction, such as the psychological or socioeconomic factors that may influence human behavior.”
In turn, these insights can be used to develop solutions for healthcare providers (hospitals, MDs, psychiatrists), insurance companies, government agencies, and businesses within the industry to help treat patients and more accurately predict future addiction based on key trigger points.
IBM Research is tackling this challenge as part of the “Science for Social Good” initiative in partnership with IBM Watson Health. The program has developed biometric tracking for users similar to fitness tracking apps. For instance, consider an athlete who is seriously injured and prescribed opioids for the pain. Throughout treatment, AI software powered by Watson can be used to monitor biometrics impacted by food and drugs being used, as well as behaviors such as breathing exercises to evaluate feedback and responses. It can evaluate that data against collective behavior from a broad set of personas to demystify triggering factors. Insights from the data can then be used to nudge patients toward better behaviors and potentially prevent addiction from even taking hold
Improving higher education
When students drop out of college, it’s often because they lack the resources or tools necessary to succeed. Researchers are aiming to change that. With AI, it is now possible to predict what tools, study aids, and support might provide students with a greater chance of passing their classes, using cognitive systems paired with technology like IBM’s Watson.
On the flip side, universities can use AI to mine data from student essays, professorial testimonials, and other unstructured and structured sources to help, evaluate and improve courses, and provide academic advising for students.
“The right data and AI tools can help advisors make more effective recommendations to students based on their personalized academic records,” Dholakia explains.
With AI, these insights could be as granular as ‘It’s X percent probable that using a tutor will increase your grade by Y percent in this class.’ Or if a student is at risk of failing a class, a university could offer insights that display alternative means to study that have helped other students improve their grades.
The business impact of social good
A lot of AI use cases have been traditionally limited based on solving finite input-based problems with relatively finite outcomes, Dholakia says. But AI’s capabilities — from computer vision to classification, natural language processing, and structured deep learning — are especially adaptable to the kinds of complex social challenges that scientists, researchers, government agencies and businesses are trying to solve.
“When we’re talking about solving problems like a water crisis, opioid addiction, or reducing dropout rates, there are direct and indirect benefits for companies that have a stake, which most do,” he explains.
It requires a setup that allows for centralized management of decentralized resources, and fast, efficient processors. IBM All Flash Array with IBM Power for compute, software-defined storage as the backbone, and IBM Watson enable fast on-prem processing of massive amounts of data. IBM’s Power series hardware is designed for artificial language and machine learning—and because the state-of-the-art hardware integrates with Watson, there’s no need to install additional neural network software. It’s also ready to integrate with business applications to make them more mobile and digital friendly and offers other APIs out of the box.
“It’s a joint ecosystem between the organizations that are providers for such services, the public sector, and the technology enablers such as IBM Watson that can play a pivotal role for these organizations,” says Dholakia. “AI enables them to jumpstart innovation together, rather than exerting time to build these solutions alone.”
“Every company can add its own bit of good to the world through its AI strategies,” Dholakia says. “Taking an increased focus on leveraging technology for the greater good can go a long way — especially if we begin to look at the shared knowledge and capabilities across public and private corporations, government agencies, and the tech that enables them.”
As used in this document, “Deloitte” means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of our legal structure. Certain services may not be available to attest clients under the rules and regulations of public accounting.
Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. Content produced by our editorial team is never influenced by advertisers or sponsors in any way. For more information, contact firstname.lastname@example.org.