Verifiable Data Audit promises to deliver bitcoin-like tracking to give patients peace of mind about their personal data
Alphabet’s artificial intelligence (AI) division DeepMind continues to enhance its healthcare credentials with the arrival of a Bitcoin-like auditing process to protect the personal data of patients.
The London-based firm is calling its data verification process the “Verifiable Data Audit”. The idea is that it will give patients peace of mind with a “mathematical assurance about what is happening with each individual piece of personal data.”
It comes amid growing awareness of the value of personal data, and a loss in trust in organisation’s abilities to protect their information. The NHS for example is notorious over its shoddy handling of patient data, with numerous incidents reported over the past few years.
“Data can only benefit society if it has society’s trust and confidence, and here we all face a challenge,” blogged Deepmind. “Imagine a service that could give mathematical assurance about what is happening with each individual piece of personal data, without possibility of falsification or omission.”
Deepmind said its working title for this project is “Verifiable Data Audit” for DeepMind Health. It said its effort was to provide the health service with technology that can help clinicians predict, diagnose and prevent serious illnesses.
According to Deepmind, a panel of unpaid Independent Reviewers already scrutinise its healthcare work, and they commission audits, and publish an annual report with their findings.
“We see Verifiable Data Audit as a powerful complement to this scrutiny, giving our partner hospitals an additional real-time and fully proven mechanism to check how we’re processing data,” said Deepmind. “We think this approach will be particularly useful in health, given the sensitivity of personal medical data and the need for each interaction with data to be appropriately authorised and consistent with rules around patient consent.
“For example, an organisation holding health data can’t simply decide to start carrying out research on patient records being used to provide care, or re purpose a research dataset for some other unapproved use,” it said. “In other words: it’s not just where the data is stored, it’s what’s being done with it that counts. We want to make that verifiable and auditable, in real-time, for the first time.”
But how does this work in practice? Well Deepmind already partners with certain hospital as a data processor. Last December for example Imperial College Healthcare NHS Trust partnered with DeepMind to improve patient care through cutting edge digital technologies.
With Verifiable Data Audit, Deepmind will add an entry to a special digital ledger each time there’s any interaction with patient data, to allow create a log of that interaction that can be audited later if needed.
“That entry will record the fact that a particular piece of data has been used, and also the reason why – for example, that blood test data was checked against the NHS national algorithm to detect possible acute kidney injury,” said Deepmind.
“The ledger and the entries within it will share some of the properties of blockchain, which is the idea behind Bitcoin and other projects,” it said. “Like blockchain, the ledger will be append-only, so once a record of data use is added, it can’t later be erased. And like blockchain, the ledger will make it possible for third parties to verify that nobody has tampered with any of the entries.”
Deepmind said it hopes to implement the first pieces of this later this year, but it recognises “this is really hard, and the toughest challenges are by no means the technical ones.”
DeepMind was purchased by Google for $400 million (£242m) in 2014 and is thought to employ around 400 people at its King’s Cross office. They are split into two divisions; one which focuses on computer science research and an ‘applied division’ which builds AI-based products and services designed for real-world applications.
The DeepMind team was the centre of some controversy in 2016 after it signed an agreement with the NHS, giving it access to the sensitive data of around 1.6 million patients from three NHS Trust hospitals.
Since then, it has worked with Google to slash the amount of power needed to cool its data centres by 40 percent; created a system that uses deep learning to navigate the London underground; and created a computer model that generates natural sounding speech and music.