The societies in which we live have altered the original meaning of the word “CLASSIFICATION”, by extending and mostly referring it to humans.
Such a phenomenon is apparent well beyond big data and the use of analytics. For instance, medicine and research use it making reference to old and new (e.g. emerging from DNA analysis) shared qualities and characteristics, aiming
at ever-increasing levels of personalized advertising, medicine, drugs, treatments…
Living and be treated according to one or more CLUSTER is the gist of our daily life, as personalized advertising clearly illustrates. Very often every group of “shared qualities or characteristics” even takes priority over our actual personal identity. For instance, due to a group of collected characteristics, we can be classified and targeted accordingly as
(potential) terrorists, poor lenders, breast cancer patients, candidates for a specific drug/product, potentially pregnant woman…
Classification based on our “characteristics” covers every corner of us (what we are and what we do, how we do), once we can be targeted at no cost as being left-handed, for instance. Yet, the power (resources, technology, network economies) to do so is quickly remaining in ever fewer hands.
The pace of classification is so rapid to have reached real time and virtual no cost for some players, while its pervasiveness is evidenced by the impact our web researches have on our personalized advertising.
The progressive switch to digital content and service makes it even faster and easier: “ Evolving integration technologies and processing power have provided organisations with the ability to create more sophisticated and indepth
individual profiles based on one's online and offline behaviours”
Today’s technologies enable unprecedented exploitation of information, being it small or big data, for any thinkable purpose, but mostly in business and surveillance with the ensuing juridical and ethical anxieties.
Algorithms are regularly used for mining data, offering unexplored patterns and deep non-causal analyses to those businesses able to exploit these advances. They are advocated as advanced tools for regulation and legal
problem solving with innovative evidence gathering and analytical tools. Yet, these innovations need to be properly framed in the existing legal background, fit in the existing set of constitutional guarantees of fundamental rights and freedoms, coherently policy related to reap the richness of big and open data and administration while empowering
equally all players.
Therefore the RIGHTS project aims at:
1) framing the main legal and ethical issues raised by the expounding use of
algorithms and classifications in
a) the information society,
b) its digital economy
c) heightened public and private surveillance;
d) Health related decisions
2) Setting the basic principles that must govern them globally in the mentioned
3) exploring additional uses of algorithms and cluster based legal-problems
solving to expand their role for public interest policies (e.g. serving
pharmacovigilance) and to empower individuals in governing their data
production and their data flow.