This thread from journalist Melissa Chan got me thinking about how generative AI tools like OpenAI's ChatGPT or Google's Bard can unwittingly be used to prop up the arguments of anti-democratic states like Russia and China.
The classic Russian disinformation playbook is to undermine confidence in proven facts to create a hazy cloud of confusion.
After all, it's in Russia's interests for us to understand the war in Ukraine as a "complex" situation that needs to be understood from "different perspectives" rather than recognising it for the war of aggression that it is.
This kind of response from ChatGPT is a classic example of "bothsidesism", where an issue is presented as more balanced than it actually is.
It states some undisputed facts but uses a passive voice - “the conflict has resulted in thousands of deaths” rather than attributing these consequences to Russia’s actions. And where Russia is criticised it is done by using language like “the Ukrainian government and Western countries have accused Russia…” or “the international community has condemned Russia’s actions” where criticism of Russia is seen as just one point of view.
Russia invaded Ukraine and has committed atrocious war crimes - including the abduction of children - which has led to the ICC issuing an arrest warrant for Vladimir Putin. But you wouldn't know that just from asking ChatGPT.
Why is that? We can't be sure, because despite the name, OpenAI isn't actually open at all. They have refused to disclose information about the training data used for the latest release of GPT-4, so we don’t know whether GPT-4’s training data included propaganda from Russia Today, Putin’s speeches or pro-Russia apologists in the Western media. Nor do we have any transparency on the rules that have been created to shape ChatGPT’s responses.
Generative AI is an incredibly powerful tool that has the potential to transform so many aspects of our lives - especially reporting and online media.
But before we hand over the keys to the newsroom to the robots, let's be clear about what's at stake.
Democracy relies on calling out authoritarianism and holding criminals to account. Let's not let AI whitewash Putin's crimes - and the same applies for the situation in Xinjiang and Tibet (as also included in Melissa Chan’s original twitter thread).
Each year I try to read at least 100 books, for no other real reason than because reading is broadly a useful and interesting thing to do and 100 is a nice round number.
I figured that if I consistently reached 100 books per year, then over a decade I would be able to read 1,000 books. And since 1,000 is an even nicer round number than 100, that seems like a rather worthwhile goal.
In practice, my reading target normally means I start by taking on ambitious biographies and long-form histories in January, but by October I'm powering through novellas, poetry compilations and anything else under about 250 pages.
One good thing about trying to read lots of books each year is that I get to read widely on all sorts of interesting topics.
I tend to read a lot more non-fiction than fiction, but have tried to start to balance that out recently.
It won't surprise anyone who knows me that I keep a database of everything I read, so drumroll please..
📊 Some key stats for the books I read in 2022:
Some of my favourite books I've read this past year include the following:
David Orrell is a Canadian mathematician who has some strong opinions about the state of the Economics profession (reader, he's not a fan. See his other book Economyths: 11 Ways Economics Gets It Wrong). A decade after the financial crisis Orrell rightly argues that economics has lost its way and needs some fresh thinking.
Orrell's thesis is twofold, firstly, that Economics sees itself as the science of scarcity when it should be about the science of money, a concept which has been overlooked in much of mainstream economic theory. And secondly, when you take a closer look at money, it is a phenomenon that has a quantum nature of its own, and can be best understood by applying principles from quantum mechanics.
For example - the concept of wave-particle duality in quantum mechanics posits that a quantum entity may behave like a wave until it is observed, at which point it behaves like a particle. It's a complicated idea to get your head around, until you consider that there are some real-life scenarios that are very similar. Take real estate: a property doesn't have a price until it is sold, and yet may change in value dramatically between sales. When the value of a property is not being observed it may behave like a wave function, responding to factors acting upon it, but when it is "observed" (i.e. a transaction is made to put an offer on the property to purchase it) it then behaves like a particle, with a defined value.
What I loved about this book was the way Orrell draws parallels between quantum theory and how we think about money, which is a fascinating way both to learn more about quantum theory and think critically about economic dogma. Would highly recommend this book or any of David Orrell's other works.
Merlin Sheldrake (who sounds like he should be the substitute Herbology teacher at Hogwarts) has written this hugely entertaining exposé about everything you didn't realise you needed to know about fungi.
Sheldrake takes the reader on a deeply-researched and somewhat poetic tour of lichen, yeast, psychedelics, and much much more. He charmingly describes mycelium, the network of threads that make up a fungi, as "ecological connective tissue, the living seam by which much of the world is stitched into relation."
By the end of this book there is a profound appreciation of just how much we don't know about one of the fundamental types of life on our planet, and it contributes to a real sense of wide-eyed wonder.
If, like me, you thought fungi had something to do with how things rotted down but were ignorant of the vital importance they can play to therapy, medicine and emerging technology, then you will very much enjoy this book.
David Graeber was an American anthropologist and anarchist who sadly passed away in 2020, widely known for his 2018 book Bullshit Jobs that looked at the existence of meaningless jobs and the harms they inflict on society. David Wengrow is a British archaeologist and Professor of Comparative Archaeology at UCL, and together David and David have written one of the meatiest (stacking up at over 700 pages) and most provocative challenges to established historical paradigms.
The book starts by arguing that the popular view on how Western civilization developed, as set out by authors like Jared Diamond, Steven Pinker, Francis Fukuyama and Yuval Noah Harari, is out of step with anthropological and archeological evidence. They then proceed to provide this evidence in spades, and show a host of various political models, including societies that switched between authoritarian and communal systems with the changing of the seasons.
The authors paint a picture of a much more diverse and nuanced picture of "development" than what is conventionally understood, and point to how our world has lost three social freedoms that were once common: the freedom to escape one's surroundings and move away, the freedom to disobey arbitrary authority, and the freedom to reimagine and reconstruct one's society in a different form. It's a well-argued and strongly-evidenced book, and suggests that much can be learned by looking into our history to find alternative models of organising society and managing political power.
Everybody's favourite vacuum cleaner inventor shares his story in this enlightening autobiography. Famously, James Dyson made 5,127 prototypes of what would ultimately become his hugely popular cyclonic vacuum cleaner, and he shares how success was far from guaranteed in the early days of building his eponymous company.
Reading this book worked its magic on me: I'm now the proud owner of a V15 Detect that makes me genuinely look forward to cleaning. More importantly though, Dyson's anecdotes about what it was like to build such a successful consumer technology brand in the UK reveals much about what it is to be an entrepreneur, the state of the tech industry in the UK, and how the UK's inability to navigate the EU's regulatory regime meant that British firms were regularly outmanoeuvred by French and German rivals.
I remember one point in the book, where once Dyson has made his fortunes he is asked by a similarly wealthy acquaintance when he will stop working - which points to a fundamental difference between British and US cultures. In Dyson's experience, many wealthy people in the UK often don't actively work once they have built successful and established business. According to Dyson, many of his peers choose to live off their passive income where possible, compared to somewhere like the US where titans of industry like Jeff Bezos or Elon Musk are driven to continually reach new heights. Maybe there is something in that which can help us understand why the UK hasn't fostered as many hyper-successful tech giants as the US?
This last one is brilliantly weird and wonderful. Jordan Hamel was the 2018 New Zealand Poetry Slam champion and represented NZ at the World Poetry Slam Champs in the USA in 2019.
His debut poetry collection is eclectic, modern, and hugely entertaining. I laughed out loud at least a dozen times reading this short collection, and would recommend it to be read widely.
One highlight was You’re not a has-been, you’re a never was! which is a great example of Hamel's biting wit, and begins thus:
I used to think I was meant for great things
until I nearly died choking on ‘Very Thin’ Vogels
watching The Mighty Ducks: D2 after
chairing a Flash Fiction Zoom conference.
Like God reaching into to my Scrabble-bag mouth
dropping mixed-grain marmite letters onto my
iPhone spelling out ‘stick to poetry’ immediately
ending the game and the indoor rhino stampede.
You get the gist. Witty, weird and wonderful.
Below is the full list of what I read in 2022, in the order I read them through the year:
My photos have had more than 10 million views on a stock image site - and I haven't earned a cent.
Believe it or not, that's the point.
I've been publishing my personal photos to the stock image platform Unsplash since 2018, where photographers upload their own images to be used for free, with no attribution required.
So far, I've only uploaded 35 images, which together have been downloaded 130,000+ times and used all kind of ways: from Sigma projects to Trello boards, and even BuzzFeed quizzes.
The vast majority of these downloads (105k) are from a single image - a waterfall in lake Taupo that you can only access by boat.
My all-time favourite use was when the UK Green Party held a local conference in Brighton, and used my photo as the promo image.It's been a great excuse to take my camera out - even if I do so infrequently!
More importantly, it's my small way of contributing to a platform that I've benefited hugely from for years.
Unsplash have an awesome mission, and it's by far the easiest stock photo site to find inspiration for a project.
My next big Unsplash milestone is 500k downloads... so I think it's time to take the camera out again soon!
You can check my photos out for yourself here.
Mark Zuckerberg has plenty on his plate: from legal settlements for privacy violations, trying to avoid being seen to support interference in elections, and working out how to build and promote the “Metaverse” (whatever that means) while being mocked for how rubbish it looks.
But it’s the rising threat of TikTok that is the biggest threat to the social media juggernaut that is Meta.
Facebook & Instagram make it easy for users to keep up with what their friends and favourite celebrities are up to. Both platforms are built around the “social graph”, which is the data relating to interconnections between people, their friends, and the accounts they follow and interact with.
This data is used by the newsfeed algorithm to show relevant content on each platform based on who we are connected to - whether it’s a page we follow, an update from a friend, or something that Facebook thinks we will find interesting.
By keeping users hooked on interesting content, Meta can then sell their captive attention to advertisers. And that’s why Mark Zuckerberg is a billionaire.
But TikTok uses big data & AI to recommend addictive videos from people we don't know, and never would have thought to follow. Instead of recommending content in the feed based on who we are connected to, TikTok curates a personalised feed based on the content we have watched, liked or shared on the platform in the past. Every piece of content a user watches on the platform is another datapoint to provide better recommendations.
Network effects are when the value of a platform increases for each individual user as the overall number of users grows. Other social networks benefit from network effects when more users connect with each other - after all, Instagram is pretty pointless when you aren’t following anyone, but is much more fun when you have a few dozen friends whose content is appearing in your feed, and when everyone you want to hear from is using the platform.
But TikTok is less of a social network and more of a content engine that is insanely good at finding and recommending interesting videos. You don’t have to add any friends to get value from the platform, compared to other social networks like Facebook, Instagram, Twitter and LinkedIn.
TikTok also gets the benefit of network effects from every video people interact with: which is a much smaller action for a user to take than finding and connecting with friends.
While Meta needs your social graph to build you a newsfeed that will capture your attention, TIkTok can just keep recommending you videos until the platform has worked out how to get you hooked.
Globally, average monthly engagement on TikTok is 25.7 hours per user, compared to just 16 hours for Facebook and 7.9 hours for Instagram.
In the UK, adults (18+) are spending more time on TikTok than on any other platform (closely followed by Instagram). That’s not bad for a platform that only launched properly in 2018 - compared to the 12 years Instagram has had to become the behemoth it is now.
Meta knows that the days of Facebook’s dominance of the social media landscape are over. That’s why Zuckerberg renamed the parent company of Facebook, Instagram, WhatsApp and Oculus to Meta instead of Facebook.
That’s also largely why we’ve been hearing so much about the “Metaverse” from Zuck over the past year - he needs investors to back his long-term vision, because the future sure isn’t Facebook.
It will be a long time before we know whether or not Zuckerberg’s ambitions for the “Metaverse” will work out. In the meantime, Meta needs to work out what to do with Facebook and Instagram.
Essentially, Zuckerberg's challenge ahead is to transform Facebook & Instagram:
From: follower platforms that show content based on people's social graph (i.e. friends and people/brands we follow).
Into: discovery platforms that use data and algorithms to recommend content from creators that we wouldn't have otherwise known about.
Essentially: Meta is trying to play catchup by turning Instagram into a TikTok clone - but it's an uphill battle, and mega-influencers like Kylie Jenner and Kim Kardashian have already kicked up a fuss about how Instagram is changing, forcing Meta to backtrack.
For now, Meta has had to cancel the proposed changes to Instagram - but they will have to find a way to catch up in order to stay competitive in the battle for our attention.
It won't be easy.
If Zuck is successful, Meta will continue to be the most important company that shapes how people communicate and connect.
But if he fails, then Meta will continue on a downward spiral towards irrelevance.
And meanwhile, Meta's share price is already taking a hit, after posting its first YoY quarterly revenue decline since it went public in 2012 - in large part because of declining user engagement as shown in this chart.