[michaelt]

> It has given 20,000 researchers around the world access under strict agreements that prohibit sharing data further.

To me it seems rather naive to have done that.

After all, you can't un-leak medical data. So even if the "strict agreement" included huge punishments, there's no getting the toothpaste back in the tube.

If you want to ensure compliance before a leak happens you have to (ugh) audit their compliance. And that isn't something that scales to 20,000 researchers.

Too late to do anything about it now though :(

[petterroea]

One of the favorite lessons I learned is that anything at scale has to be designed for idiots. I am pretty sure every person reading this has had days where they have done absolutely stupid things without realizing. Now assume there are thousands of users, and you could be providing tools to the smartest people in the world and still have people do stupid stuff all the time. This doesn't just apply to UX.

Then there's the question of trust. You probably have friends you know not to tell certain secrets to, because they believe they get to delegate your secrets onwards to people they trust. The further away someone is from you, the less respect they will show. Researchers have been loaning the dataset in good faith to people who they trust, but who probably didn't take the whole secrecy thing as seriously.

With 20k researchers this was inevitable. The kind of factors above need to be factored in when designing on what grounds such a dataset is to be released.

[LeifCarrotson]

"Favorite" in what sense? "Most critical" is a very different meaning of the word, usually it implies pleasure/happiness.

Internalizing that people are frequently less intelligent and less respectful and less kind and less thoughtful than you previously believed is a tragic loss of innocence and hope, not a favorable experience.

[petterroea]

Favourite as in "realizing it was an interesting aha moment". Sure, it's a depressing loss of innocence. But on the other hand I always love learning things where I feel like I'm closer to knowing what I'm doing. Not that I think I'll ever get there, it's an ever lasting journey

[hulitu]

> One of the favorite lessons I learned is that anything at scale has to be designed for idiots

And in the end it is designed _by_ idiots and only idiots find it usable.

[ACCount37]

Not giving the data to researchers means not getting the scientific benefits from that data. Which was the point of collecting that data in the first place.

Reckless harm prevention is the root of many evils.

[nxobject]

As a biostatistician who's touched epidemiological studies, I'd argue losing the trust of participants and the public is one of the biggest threats to the viability of the whole research enterprise. It's reckless to jeopardize that as well. Conversely, this dataset will be mined for at least 30-50 years - there are an infinite number of questions that can be asked of this dat. Given that timescale, I think a little delay here is acceptable.

[Cynddl]

It's not a zero-sum game, you can both protect people and reap the benefits of health data. Many countries have much safer approaches. UK Biobank typically leads with the scale of the data, but not with its infrastructure.

[bonesss]

That’s a false dichotomy.

Sensitive research systems thread that needle by giving remote access to researchers with the data in the control and supervision of the responsible organization. Strong internal data access controls and data siloing alongside strict verified extraction routines. Specifically: limited project-dedicated DB access, full logging of data interactions, and full lockouts/freezes if something feels off.

‘The five safes’ is a good presentation from the NHS(?) a decade ago covering the approaches.

Data publishing restrictions around health data aren’t reckless. Modern computing and digital permanence mean we have to be extra cautious.

[ACCount37]

No, this is a real tradeoff.

Any friction you add to "access the data" process makes it harder for legitimate researchers to get access to, and get benefits from that data.

So, at what point do stricter data controls begin to choke you at the throat?

[blitzar]

We have dozens of data / db startups - kinda odd that there isnt one (I have seen) that focuses on this problem.

Perhaps our future ai overlords will feel its important to compartmentalise, and log data access more agressively.

[SilverElfin]

That’s insane. And what does researcher even mean - some random university student? What would they know about securing that data? I wonder if the people whose data is out there even know this is happening

[7bees]

The people involved are volunteers. The rules for getting access are readily available, and clearly don't include "some random university student": https://www.ukbiobank.ac.uk/about-us/how-we-work/access-to-u...

[siva7]

They clearly do include "some random student" as the data can be shared with others from the eligible research group which are almost always university students who have zero clue about itsec.

[globular-toast]

I worked in this field. It's not just the students. Hardly anyone seemed to understand how and why you would keep data out of a git repo.

[nxobject]

I'm curious – in which context? I've worked on NIH-funded grants in academic medical centers, throughout the research lifecycle, and I've seen how both stringently data management plans are vetted, and how annual IRB certification drills the basics even into the oldest tech-phobic investigators.

That being said, I may be as pessmistic as you are: I don't think people right now grasp how standards for deidentification may no longer be enough, and how easy and automated deanonymization changes everything. Unfortunately, cuts to federal science agencies means that I doubt any well-informed guidance will come soon.