IBM is channeling its science and tech expertise into tackling some of the world’s biggest problems.
On Wednesday, the tech giant announced the launch of Science for Social Good, a new program that partners IBM researchers with postdoctoral academic fellows and nonprofits to take on societal issues through data.
With the new initiative, IBM announced 12 projects planned for 2017. Each Science for Social Good project aligns with one or more of the 17 Sustainable Development Goals, the United Nations’ blueprint to address some of the globe’s biggest inequalities and threats by the year 2030.
Science for Social Good covers issues like improving emergency aid and combating the opioid crisis, and the projects all use data science, analytics, and artificial intelligence to develop solutions.
“The projects chosen for this year’s Social Good program cover predicting new diseases, alleviating illiteracy and hunger, and helping people out of poverty.”
One project is called Emergency Food Best Practice: The Digital Experience, which plans to compile emergency food distribution best practices and share it with nonprofits through an interactive digital tool. IBM will partner with nonprofit St. John’s Bread & Life to develop the tool based on the nonprofit’s distribution model, which helps the organization seamlessly serve more than 2,500 meals each day in New York City.
Another project is called Overcoming Illiteracy, which will use AI to allow low-literate adults to “navigate the information-dense world with confidence.” The project hopes to decode complex texts (such as product descriptions and manuals), extract the basic message, and present it to users through visuals and simple spoken messages. While this project doesn’t solve the global literacy crisis, it will allow low-literate adults engage with text independently.
“The projects chosen for this year’s Social Good program cover an important range of topics — including predicting new diseases, promoting innovation, alleviating illiteracy and hunger, and helping people out of poverty,” Arvind Krishna, director of IBM Research, said in a statement. “What unifies them all is that, at the core, they necessitate major advances in science and technology. Armed with the expertise of our partners and drawing on a wealth of new data, tools and experiences, Science for Social Good can offer new solutions to the problems our society is facing.”
Six pilot projects were conducted in 2016 in order to develop the Science for Social Good initiative. These projects covered a broad range of topics, such as health care, humanitarian relief, and global innovation.
A particularly successful project used machine learning techniques to better understand the spread of the Zika virus. Using complex data, the team developed a predictive model that identified which primate species should be targeted for Zika virus surveillance and management. The results of the project are now leading new testing in the field to help prevent the spread of the disease.
To learn more about current and past projects, visit the Science for Social Good website.