Preparing the Smart Machine Platform and Data Analysis Tools for Tomorrow’s Workers
In the future, they will determine the precise date when the traditional notion of privacy expired — probably some moment in 1999. It will take a couple of decades at least for humanity to comprehend the abilities and reach of modern surveillance, and the unfathomable amount of data being generated and collected.
For example, satellites can now identify objects as small as 50 centimeters across, according to X Prize Foundation founder Nick Diamandis. Diamandis is quoted by IDG News Service’s James Niccolai in a September 24, 2015 article. The researcher states that data analysis systems such as IBM’s Watson are the only way to extract useful information from the enormous stores of data we now collect.
Diamandis predicts that we are approaching what he calls “perfect data,” the point at which everything that happens is recorded and made available for mining. He offers two examples: self-driving cars that scan and record their environment constantly, and a fleet of low-flying drones able to capture video of someone perpetrating or attempting crimes as they occur.
Does this mean we should all don our tinfoil hats and head for the hills? Far from it. Technology is neutral — and that applies just as well to scary, Big Brother technology. The data-rich world of tomorrow holds much more promise than peril. From climate change to cancer cures, Big Data is the key to solutions that will impact the world. But this level of data analytics will require machine architectures smart enough and fast enough to process all that data, as well as access tools that humans can use to make sense of the data.
Big Data has value only if decision-makers have the tools they need to access and analyze the data. First off, this requires a platform on which the tools can run. IBM envisions Watson as the platform for data-driven Artificial Intelligence applications, as The New York Times’ Steve Lohr reports in a different September 24, 2015 article. Watson is being enhanced with language understanding, image recognition, and sentiment analysis. These human-like capabilities are well-suited to AI apps, which IBM refers to as “cognitive computing.”
IBM’s Watson includes natural language processing of questions that balances evidence against hypotheses to generate a confidence level for each proposed answer. Source: IBM.
Healthcare is expected to be one of the first beneficiaries of cognitive computing. For example, Johnson & Johnson is teaming with IBM and Apple to develop a “virtual coach” for patients recovering from knee surgery. In a September 25, 2015 article in The Wall Street Journal, Steven Norton quotes Johnson & Johnson CIO Stuart McGuigan stating that the system’s goal is to “predict patient outcomes, suggest treatment plans, and give patients targeted encouragement.
