Artificial Intelligence is getting smarter, the robots in charge of hiring, a legally-binding treaty to remove plastics from the environment finds its legs.
This edition brings you links to the most interesting fun panels on AI, in Davos. Also the full-interview with Steve MacFeely, on why we need a UN data governance agency.
Scroll all the way down.
Become a paid subscriber.
Data Governance Needs its Own Agency
Interview with Steve MacFeely, Director of Data and Analytics at the World Health Organisation and Chair of the Chief Statisticians Group of the United Nations System
We spoke about the upcoming UN Statistics Commission meeting that begins on the 23rd of February, in New York. The heads of all international organizations and national statistics offices will discuss a wide range of issues, and this year health is at the top of the agenda, with a full-day dedicated to it.
We also talked about the right fora to discuss data governance, trade in services, and the necessary institutional framework to address AI risks and benefits.
Then there is the Summit of the Future in September where the UN Statistics Commission will have a role as data governance is central to the current conversation.
Interview has been lightly edited for length and clarity.
UN Data Governance in the Spotlight
Maya Plentz - Tell us what is in store for 2024?
Steve MacFeely - In February we begin the big international calendar with the UN Statistics Commission. That begins on the 23rd of February in New York.
There you'll have all of the international organizations, but you'll also have the heads of all the national statistical offices discussing a wide range of issues, but including health this year.
Health is on the agenda, and perhaps also of great interest to WHO, and to me personally, on the 23rd there'll be a full day dedicated to international data governance which is something I've been working on as well as the Chair of the Chief Statisticians Group at the UN.
This is an area that's really attracting a lot of attention, in fact I'll be in Davos speaking on the same issue so you can see around the world there's growing interest around data governance because that's really impacting AI, because data are the fuel that's really driving AI and there's growing concerns about the governance.
I mean we've been using AI in different forms for years because basically any model you could classify as artificial intelligence So one of the big issues, like I mentioned, is data. The quality of the data feeding into it is critically important. Not only your own data for what you're doing, but the data that was used to build the model in the first place. In other words, the training data.
One of the concerns we always have is if the training data have introduced biases into the model, then those biases are hard-coded in thereafter. Whether it's gender, whether it's ethnicity, whether it's some sort of bias regarding developmental status, there could be many.
It's not that this is new.
Almost every dataset has biases, but you need to be aware of what those biases are so that you can try and correct for them, or at least be aware of them when you're doing the analyses.
One of the big challenges with large language models is that the data are so vast, it's very hard to understand what data is actually been training the model. And that makes it more challenging to understand what the biases are. And then that, as a statistician, makes it more difficult to correct for or mitigate against those biases.
Maya Plentz - And also the question of queries, right? Making the right queries to this data. If you have this really vast body which you don't know where the data came from, how was it trained, from where this data was gathered, how can you possibly do a good query too. Good queries would come from understanding what body of knowledge these models were trained on, right?
Steve MacFeely - Well, that appears to be one of the challenges too, is that depending on the query that you ask, you could ask what appear to be similar queries, or at least to you as a human appear to be reasonably similar queries, and yet you get quite different answers.
And that's one of the things that we have to understand more is how the questions that we're asking of AI are actually being interpreted by the model.
And why are they giving sometimes quite similar answers, but other times what appear to be quite different answers?
And that's a worry, you know, like if I don't ask exactly the right question, then I get this crazy answer.
I mean, it's a bit like it's almost going back to Hitchhiker's Guide to the Galaxy.
You know, now we know the answer to life, the universe and everything.
The problem is we don't know the question.
It's almost a challenge that we're facing now.
We're getting answers, but maybe we haven't asked the right question.
Maya Plentz - So what else is going to happen in Davos next week? Because the world converges there and data governance, as you said, is becoming very, very important within international organizations. It always has been, but now the conversation has transpired around, from International organizations to the private sector, data governance is the talk of the town.
Steve MacFeely - It sure is. So last year, in the middle of last year, the Chief Executives Board of the UN published a paper called International Data Governance: Pathways to Progress, which set out a view from the UN Secretariat on the importance of data governance.
And then also kind of what steps could be taken to try and improve the situation.
But that's a position paper.
Now we need countries to decide if this is something that they want to pursue.
It's not an easy topic because, across the world, there's at least three different views or perspectives around data governance.
Here in Europe, you have very much the kind of human rights centered approach, protecting the rights of the individual. In Asia, we see much more a nationalistic view, which is more about the state perspective and the individuals are sacrificed towards that.
And then in the US, we really see the private sector kind of laissez-faire approach.
And it's not clear how to reconcile these views.
But if we're talking about trade in services, if we're talking about… almost anything we do now involves the sharing of information.
So how do we share information around the world across those different perspectives that still allows us to protect against misinformation, disinformation, and also protects the individual rights of people to make sure that their rights aren't being abused as we do that.
So data governance is huge because the entire future of global commerce, human rights, national security, they all hang on the balance around data governance.
Maya Plentz - Yes, that's a very good point you make there. What kind of system there is within the United Nations to discuss this? You say that country members need to get together and now balance these three possibilities of looking at data governance. Which one is going to prevail or should they prevail? Or they should find a perfect equilibrium, which is sort of the topic in some ways. But what would be the forum for this to happen, actually? Is there a forum already? Would we need to create another forum?
Steve MacFeely - Well, you've hit the nail on the head, Maya. This is the big question.
Where do we discuss this issue? I t certainly already has surfaced in the discussions around the Global Digital Compact and in fact if you look at the policy brief for that you'll see in section F there's a large section dedicated to data governance but we would argue as data people that actually data are so important it needs to be discussed in and of itself —- it's not just a subset of digital it's not a subset of something else —- it's actually a policy issue in and of itself so one of the questions is, are data now sufficiently important that they should be part of the Summit of the Future that will be coming this autumn just after the General Assembly?
Does it need an institution of its own?
Does it belong somewhere else?
So like this is one of the other questions around data governance is where does it belong?
Who's going to take responsibility for it?
Is it a subset of a different conversation or is it a conversation on its own?
And that's an open question.
So you have the issue itself and then who's going to take ownership of the question?
Maya Plentz - Yes, that is a big question, but it's a question that perhaps needs its own institutional framework, to speak just about data governance itself, because otherwise it can easily get hijacked by different interests.
Steve MacFeely - Yeah, possibly. I mean, or simply, I've been drawing analogies with atomic energy.
After Hiroshima and Nagasaki, the world had to very quickly adapt to the reality that atomic energy existed. So you had this new technology that had the potential for enormous benefit, but also the potential of enormous destruction.
Very quickly, science and politics had to coalesce and realize that they needed an international atomic agency, because they realized they had to manage this power, this technology for the global good.
I would argue there's a lot of striking parallels with digital data.
It has the potential for enormous destruction, but potential for enormous benefit.
Politics and science need to coalesce and come together with an agreed view on how to manage this
Because left on its own, it's too fragmented, it's ungoverned.
And I really think it's an accident waiting to happen if we don't kind of put some sort of framework around data.
Maya Plentz - Right, and there is the conversation too, this past June, when the UK Secretary of State for Foreign Affairs, then James Cleverly, went to the UN Security Council and asked about the possibility of creating a new agency dedicated to artificial intelligence. Is that what we're talking about here, data governance meaning artificial intelligence?
Steve MacFeely - I mean, data is crucially important for artificial intelligence.
But it's not just about artificial intelligence.
I mean, data are crucially important for almost everything we do now.
I mean, on your telephone, you're generating masses of data every minute.
You're also consuming massive amounts of information every time you download information, every time you stream.
So data is driving so much of what we do that we take it for granted today.
And that's really where the challenge is.
Who decides what the rules are?
Who decides what's best practice?
What's safe?
At what point does risk become misuse?
Where does misuse become abuse?
None of these things are clear.
And again, it's wrapped up in culture, it's wrapped up in ideology, so these are complex issues.
So the UN has now finally expressed a view that this is sufficiently important that it needs to be discussed but it hasn't been at all prescriptive. It kind of put out this issues paper and said this is why it's important these are the risks of not discussing this, here is perhaps a way forward to at least get the discussion going but it's not up to the UN to tell countries what to do, let alone tell private enterprise what to do or individuals.
So all of these groups need to coalesce in some fora.
And, it's back to your earlier question, what's the fora?
What's the appropriate mechanism to begin this conversation?
And arguably profoundly important.
We're living now in a data age.
And I think we're only slowly waking up to that fact.
Become the smartest person in the room. That is easy, you say. The way the discussion is being highjacked by the right-wing populists. Become a paid subscriber. So you can prove to them that you stick to the facts. Not that they care. But you do. :-)
Catch-up with WEF panels on AI, Trust, and Plastic
Sam Altman and Marc Benioff discuss trust in AI at WEF - Hanna Zlady, CNN
Watch the full panel with Altman and Benioff moderated by CNN’s Fareed Zakaria - Guardian News YT - They speak NYT lawsuit, data governance, LLM training.
Axios Ina Fried interviews Sam Altman. He is bit more relaxed here, and Ina pushes for unveiling how LLMs are being trained, change in policy at OpenAI to work with the DoD, and other risks and benefits from AI, and how ChatGPT is getting smarter.
UNEP at Davos discussing concrete steps towards a global plastics treaty. Panel with Inger Andersen, Under-Secretary-General of the United Nations and Executive Director of the United Nations Environment Programme on moving from voluntary to a legally-binding treaty, reduction, prevention, and it will include the full life-cycle of products.
For Palantir CEO the Biggest Threat is War and Peace
Alex Karp of Palantir, suffers no fools, lays it bare what he thinks about SV culture and it is quite offensive for the ones’s that care about discriminatory verbiage, “cockroach dot com”? and the fib on “weird permutations of identity politics”? He is trying to make a point about social and economic equality, how to finance prosperity. Really? The problem with billionaires philosophers is that they skipped class. There are so many gaps in their understanding of the world. It is painful to watch.
He is hawkish on AI, as most of his work is with defense, and the US DoD. He claims his family goes back 900 years in Haute-Allemagne (????) :-), and finishes by stating that a massive world-of-work dislocation is underway. AXIOS House was brimming with acolytes of the eccentric CEO.
He wraps it all up mixing Calvin and Luther in a self-congratulatory cocktail, and how GDP growth trumps crazy politics. He needs a haircut. European startups are anemic, but getting a free education, his PhD, in Germany was alright. His best advice, run slowly and get your oxygen in. :-)
In this other interview with Andrew Ross Sorkin, who has the patience of a saint, the Palantir CEO blames the elites at Davos, at the same time pledging that he is against xenophobia, and confirming that AI is a winners take all game. A reckoning, on Israel, and the displacement of workers due to the impact of AI, and higher-education astronomical cost in the US.
I told you these were the fun ones. You are welcome.
Support our work. Become a paid subscriber.
AI Impact on Jobs
IMF: 40% of Global Employment Could be Disrupted by AI - Michelle Toh, CNN
Sharon Goldman on The Pile, one of the world’s largest AI training datasets
What is data labelling?
Outsourcing the Data Labelling That Powers the AI Economy
“The “intelligence” component of AI still requires significant human input to develop its data processing capabilities. Popular chatbots like ChatGPT are pre-trained (hence, the PT in GPT). A critical phase in the pre-training process consists of supervised learning.” The Conversation
* the video is from 2023
We want to read more.
Real books.
A digital detox.
How many people to train the models? For how much?
KYLE CHAYKA is a staff writer at The New Yorker, where he writes a column on digital technology and the impact of the Internet and social media on culture.
THE ALGORITHM WILL NOT HIRE YOU”In her new book The Algorithm, journalist Hilke Schellmann investigates software that automates résumé screening and promotion recommendations, raising concerns about discrimination”, via WIRED
She reported on the use of AI in hiring for The Wall Street Journal, MIT Technology Review, and The Guardian
Journalist Hilke Schellman dives deep on how discrimination in the job market has been happening for the last decade or more, with automated recruitment platforms, with no oversight by governments, slipping under the radar of legislation that prevents discrimination by age, race, disability, and sexual orientation.
She was interviewed by WIRED, check it out.
Many HR service providers are in violation of human rights treaties. Plenty of cases where the UN agency for Human Rights should be looking at, and other regulators at the national and the EU level. A sector ripe for progress in regulation, imposing fines and forbidding some of these companies to collect data on job-seekers and create false profiles with what is mostly pseudo-science, such as facial recognition tools.
Around the World
Compliance
Google will allow consumers in Europe to stop sharing data across a select number of Google's services, including YouTube, Search, ad services, Google Play, Chrome, Google Shopping, and Google Maps. This is on response of the Digital Markets Act entry into force on the 6th of March.
Become the smartest person in the room. That is easy, you say. The way the discussion is being highjacked by the right-wing populists. Become a paid subscriber. So you can prove to them that you stick to the facts. Not that they care. But you do.
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View all episodes
By Maya PlentzArtificial Intelligence is getting smarter, the robots in charge of hiring, a legally-binding treaty to remove plastics from the environment finds its legs.
This edition brings you links to the most interesting fun panels on AI, in Davos. Also the full-interview with Steve MacFeely, on why we need a UN data governance agency.
Scroll all the way down.
Become a paid subscriber.
Data Governance Needs its Own Agency
Interview with Steve MacFeely, Director of Data and Analytics at the World Health Organisation and Chair of the Chief Statisticians Group of the United Nations System
We spoke about the upcoming UN Statistics Commission meeting that begins on the 23rd of February, in New York. The heads of all international organizations and national statistics offices will discuss a wide range of issues, and this year health is at the top of the agenda, with a full-day dedicated to it.
We also talked about the right fora to discuss data governance, trade in services, and the necessary institutional framework to address AI risks and benefits.
Then there is the Summit of the Future in September where the UN Statistics Commission will have a role as data governance is central to the current conversation.
Interview has been lightly edited for length and clarity.
UN Data Governance in the Spotlight
Maya Plentz - Tell us what is in store for 2024?
Steve MacFeely - In February we begin the big international calendar with the UN Statistics Commission. That begins on the 23rd of February in New York.
There you'll have all of the international organizations, but you'll also have the heads of all the national statistical offices discussing a wide range of issues, but including health this year.
Health is on the agenda, and perhaps also of great interest to WHO, and to me personally, on the 23rd there'll be a full day dedicated to international data governance which is something I've been working on as well as the Chair of the Chief Statisticians Group at the UN.
This is an area that's really attracting a lot of attention, in fact I'll be in Davos speaking on the same issue so you can see around the world there's growing interest around data governance because that's really impacting AI, because data are the fuel that's really driving AI and there's growing concerns about the governance.
I mean we've been using AI in different forms for years because basically any model you could classify as artificial intelligence So one of the big issues, like I mentioned, is data. The quality of the data feeding into it is critically important. Not only your own data for what you're doing, but the data that was used to build the model in the first place. In other words, the training data.
One of the concerns we always have is if the training data have introduced biases into the model, then those biases are hard-coded in thereafter. Whether it's gender, whether it's ethnicity, whether it's some sort of bias regarding developmental status, there could be many.
It's not that this is new.
Almost every dataset has biases, but you need to be aware of what those biases are so that you can try and correct for them, or at least be aware of them when you're doing the analyses.
One of the big challenges with large language models is that the data are so vast, it's very hard to understand what data is actually been training the model. And that makes it more challenging to understand what the biases are. And then that, as a statistician, makes it more difficult to correct for or mitigate against those biases.
Maya Plentz - And also the question of queries, right? Making the right queries to this data. If you have this really vast body which you don't know where the data came from, how was it trained, from where this data was gathered, how can you possibly do a good query too. Good queries would come from understanding what body of knowledge these models were trained on, right?
Steve MacFeely - Well, that appears to be one of the challenges too, is that depending on the query that you ask, you could ask what appear to be similar queries, or at least to you as a human appear to be reasonably similar queries, and yet you get quite different answers.
And that's one of the things that we have to understand more is how the questions that we're asking of AI are actually being interpreted by the model.
And why are they giving sometimes quite similar answers, but other times what appear to be quite different answers?
And that's a worry, you know, like if I don't ask exactly the right question, then I get this crazy answer.
I mean, it's a bit like it's almost going back to Hitchhiker's Guide to the Galaxy.
You know, now we know the answer to life, the universe and everything.
The problem is we don't know the question.
It's almost a challenge that we're facing now.
We're getting answers, but maybe we haven't asked the right question.
Maya Plentz - So what else is going to happen in Davos next week? Because the world converges there and data governance, as you said, is becoming very, very important within international organizations. It always has been, but now the conversation has transpired around, from International organizations to the private sector, data governance is the talk of the town.
Steve MacFeely - It sure is. So last year, in the middle of last year, the Chief Executives Board of the UN published a paper called International Data Governance: Pathways to Progress, which set out a view from the UN Secretariat on the importance of data governance.
And then also kind of what steps could be taken to try and improve the situation.
But that's a position paper.
Now we need countries to decide if this is something that they want to pursue.
It's not an easy topic because, across the world, there's at least three different views or perspectives around data governance.
Here in Europe, you have very much the kind of human rights centered approach, protecting the rights of the individual. In Asia, we see much more a nationalistic view, which is more about the state perspective and the individuals are sacrificed towards that.
And then in the US, we really see the private sector kind of laissez-faire approach.
And it's not clear how to reconcile these views.
But if we're talking about trade in services, if we're talking about… almost anything we do now involves the sharing of information.
So how do we share information around the world across those different perspectives that still allows us to protect against misinformation, disinformation, and also protects the individual rights of people to make sure that their rights aren't being abused as we do that.
So data governance is huge because the entire future of global commerce, human rights, national security, they all hang on the balance around data governance.
Maya Plentz - Yes, that's a very good point you make there. What kind of system there is within the United Nations to discuss this? You say that country members need to get together and now balance these three possibilities of looking at data governance. Which one is going to prevail or should they prevail? Or they should find a perfect equilibrium, which is sort of the topic in some ways. But what would be the forum for this to happen, actually? Is there a forum already? Would we need to create another forum?
Steve MacFeely - Well, you've hit the nail on the head, Maya. This is the big question.
Where do we discuss this issue? I t certainly already has surfaced in the discussions around the Global Digital Compact and in fact if you look at the policy brief for that you'll see in section F there's a large section dedicated to data governance but we would argue as data people that actually data are so important it needs to be discussed in and of itself —- it's not just a subset of digital it's not a subset of something else —- it's actually a policy issue in and of itself so one of the questions is, are data now sufficiently important that they should be part of the Summit of the Future that will be coming this autumn just after the General Assembly?
Does it need an institution of its own?
Does it belong somewhere else?
So like this is one of the other questions around data governance is where does it belong?
Who's going to take responsibility for it?
Is it a subset of a different conversation or is it a conversation on its own?
And that's an open question.
So you have the issue itself and then who's going to take ownership of the question?
Maya Plentz - Yes, that is a big question, but it's a question that perhaps needs its own institutional framework, to speak just about data governance itself, because otherwise it can easily get hijacked by different interests.
Steve MacFeely - Yeah, possibly. I mean, or simply, I've been drawing analogies with atomic energy.
After Hiroshima and Nagasaki, the world had to very quickly adapt to the reality that atomic energy existed. So you had this new technology that had the potential for enormous benefit, but also the potential of enormous destruction.
Very quickly, science and politics had to coalesce and realize that they needed an international atomic agency, because they realized they had to manage this power, this technology for the global good.
I would argue there's a lot of striking parallels with digital data.
It has the potential for enormous destruction, but potential for enormous benefit.
Politics and science need to coalesce and come together with an agreed view on how to manage this
Because left on its own, it's too fragmented, it's ungoverned.
And I really think it's an accident waiting to happen if we don't kind of put some sort of framework around data.
Maya Plentz - Right, and there is the conversation too, this past June, when the UK Secretary of State for Foreign Affairs, then James Cleverly, went to the UN Security Council and asked about the possibility of creating a new agency dedicated to artificial intelligence. Is that what we're talking about here, data governance meaning artificial intelligence?
Steve MacFeely - I mean, data is crucially important for artificial intelligence.
But it's not just about artificial intelligence.
I mean, data are crucially important for almost everything we do now.
I mean, on your telephone, you're generating masses of data every minute.
You're also consuming massive amounts of information every time you download information, every time you stream.
So data is driving so much of what we do that we take it for granted today.
And that's really where the challenge is.
Who decides what the rules are?
Who decides what's best practice?
What's safe?
At what point does risk become misuse?
Where does misuse become abuse?
None of these things are clear.
And again, it's wrapped up in culture, it's wrapped up in ideology, so these are complex issues.
So the UN has now finally expressed a view that this is sufficiently important that it needs to be discussed but it hasn't been at all prescriptive. It kind of put out this issues paper and said this is why it's important these are the risks of not discussing this, here is perhaps a way forward to at least get the discussion going but it's not up to the UN to tell countries what to do, let alone tell private enterprise what to do or individuals.
So all of these groups need to coalesce in some fora.
And, it's back to your earlier question, what's the fora?
What's the appropriate mechanism to begin this conversation?
And arguably profoundly important.
We're living now in a data age.
And I think we're only slowly waking up to that fact.
Become the smartest person in the room. That is easy, you say. The way the discussion is being highjacked by the right-wing populists. Become a paid subscriber. So you can prove to them that you stick to the facts. Not that they care. But you do. :-)
Catch-up with WEF panels on AI, Trust, and Plastic
Sam Altman and Marc Benioff discuss trust in AI at WEF - Hanna Zlady, CNN
Watch the full panel with Altman and Benioff moderated by CNN’s Fareed Zakaria - Guardian News YT - They speak NYT lawsuit, data governance, LLM training.
Axios Ina Fried interviews Sam Altman. He is bit more relaxed here, and Ina pushes for unveiling how LLMs are being trained, change in policy at OpenAI to work with the DoD, and other risks and benefits from AI, and how ChatGPT is getting smarter.
UNEP at Davos discussing concrete steps towards a global plastics treaty. Panel with Inger Andersen, Under-Secretary-General of the United Nations and Executive Director of the United Nations Environment Programme on moving from voluntary to a legally-binding treaty, reduction, prevention, and it will include the full life-cycle of products.
For Palantir CEO the Biggest Threat is War and Peace
Alex Karp of Palantir, suffers no fools, lays it bare what he thinks about SV culture and it is quite offensive for the ones’s that care about discriminatory verbiage, “cockroach dot com”? and the fib on “weird permutations of identity politics”? He is trying to make a point about social and economic equality, how to finance prosperity. Really? The problem with billionaires philosophers is that they skipped class. There are so many gaps in their understanding of the world. It is painful to watch.
He is hawkish on AI, as most of his work is with defense, and the US DoD. He claims his family goes back 900 years in Haute-Allemagne (????) :-), and finishes by stating that a massive world-of-work dislocation is underway. AXIOS House was brimming with acolytes of the eccentric CEO.
He wraps it all up mixing Calvin and Luther in a self-congratulatory cocktail, and how GDP growth trumps crazy politics. He needs a haircut. European startups are anemic, but getting a free education, his PhD, in Germany was alright. His best advice, run slowly and get your oxygen in. :-)
In this other interview with Andrew Ross Sorkin, who has the patience of a saint, the Palantir CEO blames the elites at Davos, at the same time pledging that he is against xenophobia, and confirming that AI is a winners take all game. A reckoning, on Israel, and the displacement of workers due to the impact of AI, and higher-education astronomical cost in the US.
I told you these were the fun ones. You are welcome.
Support our work. Become a paid subscriber.
AI Impact on Jobs
IMF: 40% of Global Employment Could be Disrupted by AI - Michelle Toh, CNN
Sharon Goldman on The Pile, one of the world’s largest AI training datasets
What is data labelling?
Outsourcing the Data Labelling That Powers the AI Economy
“The “intelligence” component of AI still requires significant human input to develop its data processing capabilities. Popular chatbots like ChatGPT are pre-trained (hence, the PT in GPT). A critical phase in the pre-training process consists of supervised learning.” The Conversation
* the video is from 2023
We want to read more.
Real books.
A digital detox.
How many people to train the models? For how much?
KYLE CHAYKA is a staff writer at The New Yorker, where he writes a column on digital technology and the impact of the Internet and social media on culture.
THE ALGORITHM WILL NOT HIRE YOU”In her new book The Algorithm, journalist Hilke Schellmann investigates software that automates résumé screening and promotion recommendations, raising concerns about discrimination”, via WIRED
She reported on the use of AI in hiring for The Wall Street Journal, MIT Technology Review, and The Guardian
Journalist Hilke Schellman dives deep on how discrimination in the job market has been happening for the last decade or more, with automated recruitment platforms, with no oversight by governments, slipping under the radar of legislation that prevents discrimination by age, race, disability, and sexual orientation.
She was interviewed by WIRED, check it out.
Many HR service providers are in violation of human rights treaties. Plenty of cases where the UN agency for Human Rights should be looking at, and other regulators at the national and the EU level. A sector ripe for progress in regulation, imposing fines and forbidding some of these companies to collect data on job-seekers and create false profiles with what is mostly pseudo-science, such as facial recognition tools.
Around the World
Compliance
Google will allow consumers in Europe to stop sharing data across a select number of Google's services, including YouTube, Search, ad services, Google Play, Chrome, Google Shopping, and Google Maps. This is on response of the Digital Markets Act entry into force on the 6th of March.
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Apple removes a light-based pulse oximetry technology used to measure oxygen levels in Apple Watch Series 9 and Apple Watch Ultra 2 smartwatches to comply with a ban in the US after a company in Europe sued saying it violated a patent they held.
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