This week, in the Roundup: Who would win in a cage fight between Elon Musk and Mark Zuckerberg? We may be about to find out. Elsewhere, Reddit goes dark and farewell to the humble autocorrect fail.
News
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There’s a new trend sweeping tech. No, not generative AI. Nope, not swingeing cost-cuts. Uh-uh, no, the new craze taking root in the C Suite is getting swole. Jeff Bezos now looks like the uncle you avoid at Christmas, unless you want to hear about the calf-leather upholstery in his new Corvette, or get forced to invest in his MLM scheme selling protein shakes.
The Zuck is certainly not impervious, either. The once mild-mannered Meta CEO is now morphing into some kind of Jean-Claude Van Damme-esque martial arts killer.
It’s all the funnier therefore, that Elon Musk has offered himself up for a fight with Zuckerberg, writes Alex Heath at The Verge, as part of their ongoing beef over Meta’s planned Twitter competitor.
In more serious news, critics of the UK’s Online Safety Bill are urging the government to include provisions allowing independent researchers access to social media data, according to The Guardian’s Dan Milmo.
There are concerns that, as things stand, the bill would do little to make the workings of social media algorithms transparent to the outside world.
The bill is slowly winding its way through parliament, but already has met resistance from a litany of civil society groups concerned, simultaneously, that the government is regulating too much and too little.
Already, proposals within the bill to define “legal but harmful” content have been walked back, with critics worried that policing legal speech should not be within the remit of democratic governments.
Analysis
Say what you will about Elon Musk’s ownership of Twitter, there’s no doubt he’s an innovator. So many of those things that people currently hate about social media seem to be traceable directly to him. Paid verification on Facebook and Instagram? Twitter did it first. Charging for API access like Reddit? Ditto.
The latter of these developments, especially, has not gone down well. Some developers producing software that relies on Reddit’s API are looking at a yearly bill that could reportedly amount to tens of millions of dollars. After it was pointed out that some of the affected applications help users with disabilities such as visual impairments to use Reddit (at no cost to Reddit themselves) these got a special waiver. The rest weren’t so lucky.
Unlike other platforms, Reddit relies on a community of volunteers to moderate content. As Rory Mir of the Electronic Frontier Foundation writes, in the last few weeks, mods angry at the changes have taken over 8,000 subreddits private in protest, effectively blacking-out the platform. Reddit bigwigs have shown no intention to change their API pricing structure, meaning this impasse isn’t going to be broken any time soon.
A recent report from the Office of the Director of National Intelligence has detailed the routine acquisition of personal data by US intelligence agencies.
According to Vox’s Sara Morrison, agencies such as the FBI and CIA have been purchasing this data, legally, from data brokers for years. And what’s more, it’s perfectly possible to match this anonymized data to IRL identities.
This was something of an open secret as spending by these agencies is documented and often publicly available. But now calls are growing to establish why this data is being bought and how it is being used.
The role of data brokers is also coming under greater scrutiny. In February, the Washington Post revealed that data brokers were selling data aggregated from mental health apps, some of which included “personally identifiable data featuring names, addresses and incomes, with one data-broker sales representative pointing to lists named ‘Anxiety Sufferers’ and ‘Consumers With Clinical Depression in the United States.’ Some even offered a sample spreadsheet.”
AI
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We all know that AI needs data. AI is essentially an enormous game of connect the dots – the more dots accurately connected, the more precise the final picture. But making sure those dots are numbered correctly is the key. Likewise, the ability of AI to make accurate connections between different data points is dependent on accurately labeling those data points. This labeling, it turns out, is exceedingly tedious manual work.
As The Verge’s Josh Dzieza writes: “There are people classifying the emotional content of TikTok videos, new variants of email spam, and the precise sexual provocativeness of online ads. Others are looking at credit-card transactions and figuring out what sort of purchase they relate to or checking e-commerce recommendations and deciding whether that shirt is really something you might like after buying that other shirt. Humans are correcting customer-service chatbots, listening to Alexa requests, and categorizing the emotions of people on video calls. They are labeling food so that smart refrigerators don’t get confused by new packaging, checking automated security cameras before sounding alarms, and identifying corn for baffled autonomous tractors.”
His report about a Kenyan data labeling venture is a fascinating glimpse into this hidden world.
Fans of mid-aughts internet chuckles will be sad to hear that the days of the autocorrect fail may soon be a thing of the past. According to Caroline Mimbs Nyce at The Atlantic, Apple has announced an update to autocorrect that uses AI to understand words contextually, rather than just going on similarity.
I, for one, will ducking miss it.
