Big companies naturally accumulate more data because they have more sensors recording more stuff. This gives big companies a huge advantage. But what if you can create a searchable depository of all available data where all critical personal details are encrypted in blockchains? Then you will have democratized access for predictive analytics that could benefit all users big or small, for-profit and non-profit.
Democratized access to predictive analytics is the goal of Endor, an MIT-based group led by Yaniv Altshuler that seeks to combine AI with social physics to gain more understanding about the behaviour of big groups.
Ellen Tannam elaborates on Endor and social physics in this article from Silicon Republic:
Endor’s proprietary technology involves an automated engine that has the capability to swiftly analyse and predict complex human behavioural patterns. As opposed to building predictive models for each question, the social sphere of human behaviour can be analysed, enabling a democratisation of predictive science.
Social physics originates at the MIT Media Lab under the auspices of Prof Alex ‘Sandy’ Pentland, one of the world’s leading data scientists and a co-founder at Endor. Altshuler explained: “Social physics uses big data and artificial intelligence to build a computational theory of human behaviour, whereby even complex and dynamic behavioural patterns can be captured and predicted mathematically. Just like physical laws governing the natural universe, social physics detects patterns in the human universe.”
The predictions made also stem from “fully encrypted consumer data, ensuring that clients meet privacy and security compliance regulations at all times”, Altshuler said. “Users do not even require first-hand expertise in data science in order to operate the platform successfully.”
This democratisation of predictive analytics could see the average SME gain data analytics capabilities they once thought were out of reach. At the moment, they are being left behind. “Many modern technological advancements, including predictive analytics run on big data, only benefit the largest
enterprises,” Altshuler said. “The way to reverse this trend and democratize data science is to offer affordable solutions and popularize the accessibility of data science for members of the public without data science expertise.”
