The Biobank has recruited 500K participants from the UK, aged 40-69, between 2006-2010, to share their anonymized health data with researchers and scientist around the world. The Biobank is set up as a Scottish charity, funded by various health organizations in UK both gov’t and private.
In addition to information collected during the baseline assessment:
100K participants have worn a 24 hour health monitoring device for a week and 20K have signed up to repeat this activity.
500K participants are providing have been genotyped (DNA sequencing to determine hereditary genes)
100K participants will be medically scanned (brain, heart, abdomen, bones, carotid artery) with images stored in the Biobank
100K participants have signed up to receive questionnaires asking about diet, exercise, work history, digestive health and other medical indicators..
There’s more. Biobank is linking to electronic health records (EHR) of participants to track their health over time. The Biobank is also starting to provide blood analysis and other detailed medical measures of subjects in the study.
UK Biobank (data bank) information uses
“UK Biobank is an open access resource. The Resource is open to bona fide scientists, undertaking health-related research that is in the public good. Approved scientists from the UK and overseas and from academia, government, charity and commercial companies can use the Resource. ….” (from UK Biobank scientists page).
Somewhat like open source code, the Biobank resource is made available to anyone (academia as well as industry), that can make valid use of its data BUT any research derived from its data must be published and made freely available to the Biobank and the world.
Biobank’s papers page documents some of the research that has already been published using their data. It lists the paper on genetics of brain study mentioned above and dozens more.
Differences from Data Banks
In the original data bank post:
We thought data was only needed by AI/deep learning. That seems naive now. The Biobank shows that AI/deep learning is not the only application/research that needs data.
We thought data would be collected by only by hyper-scalars and other big web firms during normal user web activity. But their data is not the only data that matters.
We thought data would be gathered for free. Good data can take many forms, and some may cost money.
We thought profits from selling data would be split between the bank and users and could fund data bank operations. But in the Biobank, funding came from charitable contributions and data is available for free (to valid researchers).
Data banks can be an invaluable resource and may take many forms. Data that’s difficult to find can be gathered by charities and others that use funding to create, operate and gather the specific information needed for targeted research.
At the end of the article Harari talks about the need to take back ownership of our data in order to gain some control over the tech giants that currently control our data.
In part 3, Harari discusses the coming AI revolution and the impact on humanity. Yes there will still be jobs, but early on less jobs for unskilled labor and over time less jobs for skilled labor.
Yet, our data continues to be valuable. AI neural net (NN) accuracy increases as a function of the amount of data used to train it. As a result, he has the most data creates the best AI NN. This means our data has value and can be used over and over again to train other AI NNs. This all sounds like data is just another form ofcapital, at least for AI NN training.
If only we could own our data, then there would still be value from people’s (digital) exertions (labor), regardless of how much AI has taken over the reigns of production or reduced the need for human work.
Safe by cjc4454 (cc) (from flickr)What we need is data (savings) banks. These banks would hold people’s data, gathered from social media likes/dislikes, cell phone metadata, app/web history, search history, credit history, purchase history, photo/video streams, email streams, lab work, X-rays, wearables info, etc. Probably many more categories need to be identified but ultimately ALL the digital data we generate today would need to be owned by people and deposited in their digital bank accounts.
Social media companies, telecom, search companies, financial services app companies, internet providers, etc. anywhere you do business should supply a copy of the digital data they gather for a person back to that persons data bank account.
There are many technical problems to overcome here but it could be as simple as an object storage bucket, assigned to each person that each digital business deposits (XML versions of) our digital data they create for everyone that uses their service. They would do this as compensation for using our data in their business activities.
How to change data ownership?
Today, we all sign user agreements which essentially gives a company the rights to our data in perpetuity. That needs to change. I see a few ways that this change could come about
Countries could enact laws to insure personal data ownership resides in the person generating it and enforce periodic distribution of this data
Market dynamics could impel data distribution, e.g. if some search firm supplied data to us, we would be more likely to use them.
Societal changes, as AI becomes more important to profit making activities and reduces the need for human work, and as data continues to be an important factor in AI success, data ownership becomes essential to retaining the value of human labor in society.
Probably, all of the above and maybe more would be required to change the ownership structure of data.
How to profit from data?
Technical entities needing data to train AI NNs could solicit data contributions through an Initial Data Offering (IDO). IDO’s would specify types of data required and a proportion of AI NN ownership, they would cede to all data providers. Data providers would be apportioned ownership based on the % identified and the number of IDO data subscribers.
Data banks would extract the data requested by the IDO and supply it to the IDO entity for use. For IDOs, just like ICO’s or IPO’s, some would fail and others would succeed. But the data used in them would represent an ownership share sort of like a stock (data) certificate in the AI NN.
Data bank responsibilities
Data banks would have various responsibilities and would need to collect fees to perform them. For example, data banks would be responsible for:
Protecting data deposits – to insure data deposits are never lost, are never accessed without permission, are always trackable as to how they are used..
Performing data deposits – to verify that data is deposited from proper digital entities, to validate that data deposits are in a usable form and to properly store the data in a customers object storage bucket.
Performing data withdrawals – upon customer request, to extract all the appropriate data requested by an IDO, anonymize it, secure it, package it and send it to the IDO originator.
Reconciling data accounts – to track data transactions, data banks would supply a monthly statement that identifies all data deposits and data withdrawals, data revenues and data expenses/fees.
Enforcing data withdrawal types – to enforce data withdrawal types, as data withdrawals can have many different characteristics, such as exclusivity, expiration, geographic bounds, etc. Data banks would need to enforce withdrawal characteristics, at least to the extent they can
Auditing data transactions – to insure that data is used properly, a consortium of data banks or possibly data accountancies would need to audit AI training data sets to verify that only data that has been properly withdrawn is used in trying the NN. .
AI NN, tools and framework responsibilities
In order for personal data ownership to work well, AI NNs, tools and frameworks used today would need to change to account for data ownership.
Generate, maintain and supply immutable data ownership digests – data ownership digests would be a sort of stock registry for the data used in training the AI NN. They would need to be a part of any AI NN and be viewable by proper data authorities
Track data use – any and all data used in AI NN training should be traceable so that proper data ownership can be guaranteed.
Identify AI NN revenues – NN revenues would need to be isolated, identified and accounted for so that data owners could be rewarded.
Identify AI NN data expenses – NN data costs would need to somehow be isolated, identified and accounted for so that data expenses could be properly deducted from data owner awards. .
At some point there’s a need for almost a data profit and loss statement as well as a data balance sheet for at an AI NN level. The information supplied above should make auditing data ownership, use and rewards much more feasible. But it all starts with identifying data ownership and the data used in training the AI.
There are a thousand more questions that come to mind. For example
Who owns earth sensing satellite, IoT sensors, weather sensors, car sensors etc. data? Everyone in the world (or country) being monitored is laboring to create the environment sensed by these devices. Shouldn’t this sensor data be apportioned to the people of the world or country where these sensors operate.
Who pays data bank fees? The generators/extractors of the data could pay in addition to providing data deposits for the privilege to use our data. I could also see the people paying. Having the company pay would give them an incentive to make the data load be as efficient and complete as possible. Having the people pay would induce them to use their data more productively.
What’s a decent data expiration period? Given application time frames these days, 7-15 years would make sense. But what happens to the AI NN when data expires. Some way would need to be created to extract data from a NN, or the AI NN would need to cease being used and a new one would need to be created with new data.
Can data deposits be rented/sold to data aggregators? Sort of like a AI VC partnership only using data deposits rather than money to fund AI startups.
What happens to data deposits when a person dies? Can one inherit a data deposits, would a data deposit inheritance be taxable as part of an estate transfer?
In the end, as data is required to train better AI, ownership of our data makes us all be capitalist (datalists) in the creation of new AI NNs and the subsequent advancement of society. And that’s a good thing.