For centuries we’ve relied on “one size fits all” generalizations to guide decisions. For example, I hear marketers today saying “the millennial generation loves sharing everything on social media.” Many do, but I certainly know some that don’t. “Children ages 3-12 should take 2mL twice daily.” How could a 3 year old really require the same dose as a 12 year old? Guidelines like these are useful and may be founded upon careful analysis, but they toss out the diversity of the individual.
One of the promises of Big Data is the ability to make better decisions based not on estimates, but on the world as it actually is – a tremendously diverse ecology of man and machine interacting, changing moment by moment. I want to share some thoughts about a research project codenamed “Reliance Point,” featured recently in Intel Software Adrenaline, that could enable this kind of very personal analysis while still preserving our privacy.
Big Data analytics makes it possible to discover patterns as they apply to specific people, even among large populations. This is the capability behind personalized advertising, but it’s also what will enable far more effective medical treatments that account for your weight, diet, and your entire genetic profile. Just as we laugh at the primitive medical practices of our ancestors, future generations will wonder how humanity ever survived without personalized medicine. The same will be true with design, manufacturing, and science. Choices will be based on specific and often real-time data about how the world actually behaves.
The challenge is that knowledge is power. In the folklore of many cultures, knowledge of a being’s “true name” can bestow power over them. One western example is the German Rumpelstiltskin, in which the discovery of a devious imp’s name is the only way to save a child from being lost.
Personalized medicine is a noble ambition, but what will an employer or a new insurance company do with my “true name” – my genetic makeup? These are serious concerns, and today this inhibits medical research and often requires that all personal identifying information be stripped away, even if it might lead to a significant discovery.
Big Data analysis is a bit like trying to find a needle in a haystack. Do we really need to hand over the entire – mostly irrelevant – haystack to a third party just to find that valuable needle? Must we give up all of our medical histories for the sake of a new drug? Must all of our purchases be tracked to get a better coupon?
Perhaps not. Intel Labs has been exploring a project codenamed Reliance Point, developed with Intel’s Data Center Group and the Intel Science & Technology Center for Secure Computing. Reliance Point allows two parties to share and analyze data within the confines of a neutral, trustworthy computing environment. Data is cryptographically protected leveraging Intel hardware features. The two parties agree on the analytics software to be used, but neither one can see the other’s data directly. If interesting insights are found relating to specific entries, the parties can negotiate for access to just that relevant data – not the whole haystack. Because source data is never exposed with Reliance Point, it may prove unnecessary to dilute its quality by stripping away personal identifying information – this could be transformational to medical research.
We are entering a data society, and information will be among our most valuable assets. I’m excited about Reliance Point because it could break down barriers to discovery. Not just for finance and healthcare, but also e-science, security, and emerging applications around personal data. I’d like to see this technology at work for my own “small data.” Not so I can hide it from the online businesses of the world, but so I can have more say as to how it’s used. Check out the Software Adrenaline article to learn more.