If you think that fast and cheap DNA reading applies only (or even mostly) to monitoring of individuals, you do not have a real grasp of the scope and applicability of DNA sequencing.
There are enormous resources in scientific research that goes toward generating datasets. Sequencing of humans is a significant part of it, but most of that applies to medicinal uses, such as cancer genotyping (which uses sequencing to identify specifically the genotypic characteristics of a particular tumor colony so it can be treated much more effectively than just trying to guess by looking at it "from the outside"). Also, a huge new area in medicine is going to be "personalized" medicine. Medicine that's actually tailored to the specific genetic traits that YOU have, so that the chances of side-effects are reduced and effectiveness is increased.
Then there are the thousands of researchers that need to collect sequence datasets on organisms that have NOTHING to do with humans. A big chunk of this is plant genetics: crop stress tolerance (e.g. make wheat grow more reliably in colder or dryer climates, or resist disease better), natural product optimization (e.g. make canola plants produce 10% more of the kinds of oils you care about, and less of the crap you don't). Another big chunk of this research is basic science: figuring out the specific details of how evolution has progressed, or to identify the core biological processes that make organisms tick. That's core evolutionary biology and biomechanics research.
Then there's the people trying to do constructive genomics: actually build organisms that do specific things. Like modifying yeast to produce some complex bioproduct that requires a network of potentially hundreds of genes. Or creating organisms that filter waste from water. Or building algae variants that run on sunlight and produce oil.
All of these things could desperately use robust, cheap, accessible sequencing platforms. Genetic sequencing is not all about your privacy. It's a platform which has the scope to save scientists and researchers millions, and put that towards more research and better results than towards trying to scrape out a few bases from a tissue sample.
IBM is trying big time to get into the life sciences (that's wrong actually, they actually already HAVE products they market to the life sciences, like systems for large-scale data processing). It is worth billions to them, and they want to tap it.
-Laxitive