Hi,

Last week, I asked if any of you could figure out a subtle change to the newsletter. One of you got it correct. Congrats, Akshay Vishwanath! Akshay was recently recognized as one of the Top 100 African Conservation Leaders [Top 100 Youth].

What changed? I updated the logo to use a capital ‘T’ instead of a lowercase ‘t’. I thought it gives the logo a better balance.

Ok ... onto this week’s articles.

Body-editing apps on TikTok ‘trigger eating disorders’

TikTok and Instagram are promoting body-editing apps on their platforms. Body-editing apps alter body parts in different ways, such as changing the size and shape of body parts, making waists slimmer, adding muscles, and clearing up skin, among other features. These apps are mostly targeted at teens. Charities that support people with eating disorders fear that these apps are fueling an epidemic of eating disorders among the younger generation [Cristina Criddle, BBC].

Eating disorder charity Seed said it has seen a 68% rise in children and teenagers aged between 10 and 19 seeking support since the pandemic.

Danae Mercer, a health journalist with a history of disordered eating, is concerned that these apps target particularly vulnerable teens.

“Teens and young girls don’t understand these things yet, not fully. In the same way, we wouldn’t allow weight loss products to be marketed at children, we need to really push for new regulation around what apps are allowed to target vulnerable audiences. Especially when those apps edit bodies.”

TikTok already banned adverts for fasting apps and weight loss supplements last year. Eating disorder campaigners now want social media companies to ban advertisements of body-editing apps as well.

+ Beauty filters are changing the way young girls see themselves [Tate Ryan-Mosley, MIT Technology Review]

In a related article, researchers are concerned about the long-term effects that photo filters on apps like Snapchat, TikTok, and Instagram may have on teens, especially.

The face filters that have become commonplace across social media are perhaps the most widespread use of augmented reality. Researchers don’t yet understand the impact that sustained use of augmented reality may have, but they do know there are real risks—and with face filters, young girls are the ones taking that risk. They are subjects in an experiment that will show how the technology changes the way we form our identities, represent ourselves, and relate to others. And it’s all happening without much oversight.

Eye tracking can reveal an unbelievable amount of information about you

Even simple HD cameras can track eye movements and collect data about your pupil and iris reactions. Recent research shows the unbelievable amount of information this can reveal about individuals [Loz Blain, New Atlas].

But according to a 2020 research review, this data can divulge an extraordinary amount of information about you when it's crunched through advanced data analysis systems. "Our analysis of the literature," reads the paper's abstract, "shows that eye tracking data may implicitly contain information about a user’s biometric identity, gender, age, ethnicity, body weight, personality traits, drug consumption habits, emotional state, skills and abilities, fears, interests, and sexual preferences."

That's not all; "Certain eye tracking measures," says the review, "may even reveal specific cognitive processes and can be used to diagnose various physical and mental health conditions." According to Grandview Research, "the analyzed data is used to study a myriad of psychiatric and neurological conditions, such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), Parkinson‘s, Alzheimer‘s, and Schizophrenia, among others."

There’s a lot more than even the list above that your eyes reveal about you. Read the article for the full details.

Like any technology, this can be used for both good and bad. Diagnosing medical conditions is definitely positive, but this has serious privacy implications. All the big tech companies and many others are working on AR and VR technology that works with headsets and eyeglasses. Eye-tracking is one of the primary mechanisms through which interaction will happen. And past experience indicates that they will use as much personal information as they can gain from you to monetize and sell to advertisers and data brokers.

The hope is that government regulation will prevent this from happening, but regulation lags far behind technology in most countries.

Concussions in sport can now be rapidly diagnosed using spit

Concussions are the most common injury in sports. Multiple concussions over time can lead to other long-term problems like chronic traumatic encephalopathy (CTE), dementia. Diagnosing concussions accurately and managing concussions in players is still a challenge. Researchers at the University of Birmingham led a study to determine if signs of concussion could be spotted in saliva. They successfully found unique signatures indicating concussion in the saliva of male rugby players [Valentina Di Pietro and Antonio Belli, The Conversation].

Previous research we conducted had identified specific molecules in saliva which change after a concussion. The molecules we identified are called small non-coding RNAs and bring messages to other cells telling them how they should behave. These molecules can be easily detected in a lab.

But we needed to see whether these molecules could be used to diagnose concussion. Using standard molecular technology to test the saliva samples we noticed that these molecules were abundantly present immediately after a heady injury. We were able to successfully identify the presence of these molecules in minutes – moments after a concussion happened. This means it’s now possible to accurately identify concussions simply by analysing a player’s saliva.

This is great news, as concussions can be identified rapidly and more accurately, leading to better player management and the prevention and mitigation of long-term effects. Further research is being conducted to understand when it may be safe for players to return to playing after concussions and also to investigate if medical personnel can use these methods similarly in females and children.

Other interesting articles from around the web

📺 Confirmed! We Live in a Simulation [Fouad Khan, Scientific American]

I’ve read many simulation theories, but this one sounds a lot more plausible than previous articles. One argument proposed here is that computers that run simulations leave an artifact in the form of the computer’s processor speed. The processor speed limits everything else within the simulation. Similarly, the speed of light is the artifact that is manifested in our world. Khan goes deep into other telltale signs that we are probably in a simulation, including an explanation of consciousness. A fascinating read!

So, there you have it. The simplest explanation for the existence of consciousness is that it is an experience being created, by our bodies, but not for us. We are qualia-generating machines. Like characters in Grand Theft Auto, we exist to create integrated audiovisual outputs. Also, as with characters in Grand Theft Auto, our product mostly likely is for the benefit of someone experiencing our lives through us.

🏥 How does bias affect healthcare AI, and what can be done about it? [Bill Siwicki, Healthcare IT News]

The CTO of Royal Philips provides some guidance on bias in AI as it relates to the healthcare system. Here’s part of an answer – the whole interview is very insightful.

Q: What are the different ways bias can arise in healthcare AI?

A: Let me start by saying that I strongly believe AI has the potential to improve people's health and wellbeing around the world. Every patient should benefit from that. The last thing we want is for AI to perpetuate or even exacerbate some of the health disparities that exist today.

So how can bias arise? What can be easy to forget is that AI's output is shaped by the data that is fed into it. We tend to take computer-based recommendations at face value, assuming that whatever output an AI algorithm portrays is objective and impartial. The truth is, humans choose the data that goes into an algorithm, which means these choices are still subject to unintentional biases that can negatively impact underrepresented groups.

These biases can occur at any phase of AI development and deployment, whether it's using biased datasets to build an algorithm, or applying an algorithm in a different context than the one it was originally intended for.

🫀 NHS uses AI scan to detect hidden heart disease [BBC]

About 20% of those patients given a clear after a Cat scan have a heart attack within a decade. 33% of these are reclassified as high-risk upon review. Now, AI is helping to reduce these errors.

The NHS is using artificial intelligence to treat patients at risk of a heart attack, years before they strike. 

CaRi-Heart can spot minor problems undetected by routine scans, Oxford University researchers say, identifying inflammation and scarring in the lining of blood vessels that supply the heart.

[…]

“CaRi-Heart analysis can be undertaken on any Cat heart scan, hospitals don’t need to change equipment and patients don’t need another test. 

"It fits perfectly with a physician’s workflow."

Quote of the week

“I know from my own experience, these apps can be triggering. The apps make me thinner and curvier than my body, even if I trained all the time, could ever be. They eliminate my pores in a way that’s not even possible in nature. They create a ‘me’ that is, quite simply, unachievable - and they do it all with a click of a button. The impact of technology like this is immense, and honestly I don’t think we’ll see the full result of it for years”

—Danae Mercer, a health journalist with a history of disordered eating, from the article, “Body-editing apps on TikTok ‘trigger eating disorders’” [BBC]

I wish you a brilliant day ahead :)

Neeraj