Episode 214
Weird Science: Smells Like Team Spirit
On this episode of Weird Science, a missing Crypto Queen, why we like people who smell like us, fasting for your nerves, and a crime-predicting AI. Most importantly, find out why you shouldn’t drink coffee while shopping.
Hosted by Matt Armitage & Richard Bradbury
Produced by Richard Bradbury for BFM89.9
Episode Sources:
https://journals.sagepub.com/doi/abs/10.1177/00222429221109247
https://www.iflscience.com/does-intermittent-fasting-hold-the-key-to-nerve-regeneration-64267
https://gizmodo.com/national-fecal-sample-bank-health-c-diff-1849130190
Photo by Markus Spiske on Unsplash
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Transcript
Freda Liu: At the furthest reaches of science, things start to get very strange indeed. This is why Matt Armitage back with stories about soft drinks, relationship advice and personal hygiene.
Freda Liu: Where is our weird journey taking us this week.
Matt Armitage:
• Last week we spoke about hybrid retail and how it’s reshaping the way we experience the things we buy.
• This first story links to that.
• But first I have to ask you a question:
• How much coffee or other types of caffeine do you drink or eat every day?
Freda Liu: [replies]
Matt Armitage:
• I mentioned on the last show that I used to have a doom-shopping problem.
• Browsing in bed and buying stupid things late at night.
• Well, I should point out that with the exception of dark chocolate.
• And if you aren’t eating chocolate with no sugar and 100% cocoa, then you aren’t doing it right.
• I stopped taking caffeine years ago:
• You know those sci fi movies where someone is given a stimulant and the screen goes all weird?
• It looks like the character is rushing down a tunnel.
• That’s how I feel after drinking decaf coffee, let alone anything stronger.
• But it looks like it might have saved my wallet a fortune:
• A recent study published in the Journal of Marketing suggests that consuming caffeine before or during shopping increases your risk of impulse buying.
• Those measures of caffeine include coffee, tea and energy drinks amongst other sources.
• The study was led by Dipayan Biswas, a Professor of Marketing at the University of South Florida.
• And concluded that people are likely to spend 50% more money, and buy around a third more items if they consume caffeine before of during shopping.
Freda Liu: How rigorous was the study?
Matt Armitage:
• This wasn’t a case of a grad student hanging outside a 7-11 at midnight on Saturday night.
• In the first phase, the physical retail component, researchers gave out free drinks to more than 300 participating shoppers at retail stores in France and Spain.
• Half were given coffee, the other half were given water or decaf.
• I think the participants were random – they were simply shoppers at the store who agreed to share the receipts of their shopping trip.
• In the second phase, which covered online shopping, 200 business school students were recruited.
• Half avoided caffeine all day, the second half didn’t.
• They were then asked to select purchases from a list of 66 items to buy online.
• And the results were broadly similar to the physical retail group.
Freda Liu: Were there differences in the types of goods bought by the two groups?
Matt Armitage:
• Yes, it wasn’t just the amount spent and number of items bought that differed.
• And that seems to be linked to the way caffeine stimulates our nervous systems.
• It heightens our senses and makes us feel more alert. And it gives us a dopamine rush.
• That rush can in turn increase our impulsivity and decrease our self-control.
• So the control groups that stayed away from caffeine, either completed their purchases as originally intended,
• Or bought items that were more practical.
• The caffeinated groups would buy things on impulse rather than need.
• Sticking with the senses:
• I don’t know how many of our listeners know the Monty Python sketch about the funniest joke in the world?
• My dog has no nose. How does he smell? Terrible.
• I’m going to ask you another question: what do your friends smell like?
Freda Liu: [replies]
Matt Armitage:
• I know it’s a weird question. But it’s not random.
• Last week during the hybrid retail show I mentioned the way brands use signature smells as one of the defining factors of their stores.
• Like the cookie dough smell you get at Famous Amos, for example.
• Or signature scents that are used by some beauty and wellness brands.
• Because smell plays a much stronger part in our lives than most of us recognize.
• So when I asked you what your friends smell like, it wasn’t a creepy, weirdo question.
• I mean… well, anyway…
• New research by the Weizmann Institute of Science in Israel suggests that smell plays an important part in the way we build friendships.
• And that we’re more likely to form friendships with people who smell like us.
Freda Liu: It still sounds creepy…
Matt Armitage:
• I know it comes across like it’s some kind of garlic lovers’ appreciation society.
• But it seems to be much deeper and a lot more primal.
• I found this story on NS btw.
• Inbal Ravreby at the Weizmann Institute was interested in why we form those sudden strong relationships with people.
• People you feel you instantly click with and wondered, as you do,
• If it had anything to do with body odour.
• She knew that previous research had found evidence that we subconsciously sniff other people when we meet.
• We might do something like sniffing our hand – do we really do things like that?
Freda Liu: [replies]
Matt Armitage:
• The Israeli team recruited 20 pairs of same sex friends who said that they had clicked as friends in this way.
• 10 male pairs and 10 female.
• They then used an electronic nose to sniff clothing that had been worn by each subject.
• And as a control, they randomly reassigned the pairs and repeated the tests.
• And the results showed that the friend pairs smelled more alike than the random pairings.
• Then they took their hypothesis and recruited 17 further subjects who hadn’t met before.
• They took turns playing a non-verbal game with other subjects of the same sex.
• And the results were the same: participants tended to click with people who smelled more like them.
• I know this sounds very strange, but the study builds on previous research that suggests each of us has a set of social fingerprints that guides us in forming friendships and relationships with people.
Freda Liu: Like a signature genetic rule book?
Matt Armitage:
• Yes – I’m not going to go into it too deeply.
• If you are interested there’s a great article on the New Scientist website by the evolutionary psychologist Robin Dunbar.
• It’s titled the hidden rules that determine which friendships matter to us.
• In it he discusses concepts like our ceiling limit for friendships.
• That thing about most of us having 150 people as friends.
• The concept has been around for a while – it’s also know as the Dunbar number after this guy.
• Things like the 30 minute effect – that friendships work best when you don’t have to travel more than 30 minutes to meet that person socially.
• I’m about an hour away from most people, so that probably explains my social circle.
• But by and large, Dunbar’s research shows that our friends are generally very similar to us.
• In terms of gender, education, outlook, interests etc.
• You have shared hobbies and interests. The same sense of humour.
• Which also explains my social circle.
• Interestingly, in it you also see quite a few of the ingredients that have helped to build the echo chamber effect over the past few years.
• We’re shocked when other people don’t think or see things like we do because all the people and information that social media exposes us to echo our beliefs and standpoint.
• And now we can add smell to that list!
• Shall we have another smell-related story?
Freda Liu: Replies
Matt Armitage:
• This one is very relevant for us in Malaysia.
• According to researchers at the Tsinghua University in China, people who have had mosquito-borne diseases like dengue and zika.
• Are more likely to be bitten by mosquitoes in the future.
• It’s been known for a while that diseases like malaria alter our body odour.
• The malaria parasite trigger a change in our body odour that attracts mosquitoes,
• Who then carry the parasites and infect other people they bite.
• So it’s a propagation method. The Tsinghua team wanted to see if the same was true for Zika and dengue.
Freda Liu: Do we know which compounds seem to attract the mosquitoes?
Matt Armitage:
• Yes. So the research team first tested the hypothesis with mice infected with zika and dengue.
• Compared with a control group without the diseases, they found that those with the viruses were twice as likely to be bitten by mosquitoes.
• They then analysed all the compounds found on the skin of the mice.
• Which they also repeated with a group of human subjects.
• Some of whom had had either of the viruses and some who hadn’t.
• They then isolated those compounds and tested them by putting them on the backs of the mice, and on the back of human hands.
• The compound that most seemed to attract the mozzies was acetophenone which seems to be more prevalent in people who have had the disease.
• It wasn’t so much that they were surprised by the result – I think they were expecting to find something like this.
• But that they were able to isolate a single compound that attracts the flying vampires is a major breakthrough.
Freda Liu: How does this help us to reduce the risk of people being bitten in the future?
Matt Armitage:
• Well, the next step is to find ways to reduce that production of acetophenone.
• Early indications from the Chinese team are that a common acne medication called isotretinoin,
• Which causes the body to increase production of antimicrobial peptides.
• Peptides are strings of amino acids.
• That isotretinoin, by stimulating the production of the body’s antimicrobial defences, suppresses that production of acetophenone.
• Their tests showed that subjects treated with the drug were no more likely to be bitten by the mosquitoes than anyone else.
Freda Liu: After the break, a crypto fugitive and a racist robot.
BREAK
Freda Liu: Are we done with the smell related stories?
Matt Armitage:
• Yes. This next one takes us further into the exciting world of gut biomes! I imagine they smell, too.
• But we don’t have to explore that today.
• Although I did read a story this week that said we should be preserving our poop.
• So that when we’re older we can use it for faecal transplants as a way to update and reset our gut flora.
• And I read another story that suggested that faecal transplants can alleviate the symptoms of conditions like IBS for up to 3 years.
Freda Liu: replies
Matt Armitage:
• It’s ok, I’ll keep it sanitary.
• I found this story on IFL science.
• Intermittent fasting has emerged as one of the most popular weight control methods over the past few years.
• With the idea that limiting our consumption of calories to certain windows of time,
• Say eight hours a day. Can help us to lose weight, and a whole host of health benefits including reducing the risk of some cancers and metabolic diseases.
• There are lots of variations on the approach but that’s a basic method.
• A new study published in the journal Nature suggests that intermittent fasting may also help us heal damaged nerves.
Freda Liu: What treatments do we currently have for nerve damage?
Matt Armitage:
• Almost none. That’s why we hear that dreaded phrase ‘permanent nerve damage’ so often.
• The only method is surgical reconstruction of the nerves. Which is only possible for certain nerves and has a relatively small success rate.
• The study by Imperial College London took previous findings that intermittent fasting aided wound repair and stimulated the growth of new neurons.
• The discovery is linked to a metabolite in our gut called 3-Indolepropionic acid, known as IPA, which we produce naturally.
• And this metabolite is crucial in regenerating axons – the tendril-like strands at the end of nerve cells that send out the electric signals from the nerve and communicate with the rest of the body.
Freda Liu: So, in a sense you could think of nerve damage a bit like turning the Internet off?
Matt Armitage:
• A little bit.
• All the websites are still there, sitting on their servers, but without the Internet to connect them they’re not much use.
• So the question then becomes how can we get more IPA into our bodies.
• I know IPA is also a beer – that route definitely won’t work.
• One way is to stimulate our own natural production of IPA. Exercise is one way.
• And intermittent fasting seems to be another.
• In tests on mice, the Imperial College Team found that those who were put on a time restricted diet regenerated axons,
• …those nerve endings, at a 50% higher rate than mice whose diets weren’t restricted.
• The next step is to move towards to human clinical trials and the team is that as our knowledge of gut flora expands,
• We will also find other bacteria or metabolites that will help us to protect and heal the body.
Freda Liu: ok. You can do AI now. Otherwise, we’re likely to go somewhere really unpleasant
Matt Armitage:
• Ok, so on a completely different topic.
• This is another story from NS.
• An algorithm that claims to be able to predict where and when crimes are likely to take place, with an accuracy rate of 90%.
• Very Minority Report – and we know how well that turned out.
• But predicting crime is not just big business – it’s one of those unicorns of modern policing.
• We’ve covered attempts to use AI in policing a few times over the years.
• The results so far haven’t been great.
• Police and probation service AIs have had an unpleasant tendency to amplify systemic biases.
• Usually racial ones.
• There was the probation service AI that would indicate that risks of recidividism were higher if you lived in traditionally black neighbourhoods.
Freda Liu: And that would be irrespective of their criminal background?
Matt Armitage:
• Precisely.
• So someone convicted of a minor, first offence could be signalled at greater risk of repeat offending if they lived in a black neighbourhood…
• …than someone with multiple, more serious offences who lived in a traditionally white neighbourhood.
• We’ve talked about the AI-based facial recognition system that London’s Met Police had to abandon after it created multiple false-positive suspect identifications for black men and women.
• The NS article flags a Chicago police system that aimed to predict who would be most likely to be involved in a shooting, either as a victim or a perpetrator.
• The data it was based on was initially withheld. After the city was forced to reveal it, it turned out that 56% of the city’s black men aged 20 to 29 were on it.
• This new system was also based on data from Chicago – it’s the work of a team at the University of Chicago.
Freda Liu: Is this a live model or a historical one?
Matt Armitage:
ed using historical data from:• But the idea is for it to become, if not a street level predictive tool,
• Then at least one that can inform citywide strategies and priorities.
• So heading for live predictions.
• In the model, the city was divided into squares roughly 300m across.
• And it predicted where certain crimes were likely to be committed a week in advance.
• That’s the difference I think with a lot of previous systems – its targeting locations, rather than individuals.
• And another seven cities were analysed in the same way, with similar results.
• Suggesting that the tool is capable of adapting to the policing requirements of diverse towns and cities.
• But, the authors do note that the model is likely to repeat or reflect biases in the data.
Freda Liu: Typically, why do we see these biases?
Matt Armitage:
• That would be a whole series of episodes to explain fully.
• In the facial recognition system example – a lot of the early facial recognition systems were trained using commercial photo data sets.
• Which overwhelmingly skew white and male.
• So the systems – or at least early ones – had a lot of data to build up a picture of the differences between different faces.
• As long as they were white and male.
• So the accuracy rate drops off precipitously if you fall outside of those parameters.
• I don’t usually interrupt one story with another…
• Researchers at the Georgia Institute of Technology in Atlanta recently published the results of a study in biases.
• They built a virtual robot running a neural network from OpenAI called CLIP.
that OpenAI flagged CLIP in a:Freda Liu: How susceptible did the research team in Atlanta find it to be?
Matt Armitage:
• As a white male, a little worrying might be the way I describe it.
• To anyone who isn’t a white male: potentially terrifying might do it?
• The robot was trained with images of people. Different genders and ethnicities.
• Its task was to answer questions by putting the people it thought most likely to represent the answer to the question into boxes.
• Black men were 10% more likely to be selected when the command was to pack the criminal in a box.
• Latina and black women were preferred when the question was identify homemakers.
• And the system favoured men over women when asked to identify doctors.
Freda Liu: Don’t questions like that provoke bias?
Matt Armitage:
• Of course. That was the point.
• The researchers were looking to exploit and identify areas of bias.
• Ideally you want a system where the dataset is normalised to discourage those biases.
• Or it’s smart enough to realise that the results are skewed, or that the question is designed to elicit bias.
Freda Liu: Going back to the Chicago crime model. Wouldn’t data that is based on the police’s own records be more accurate?
Matt Armitage:
• Not necessarily, the NS article quotes Lawrence Sherman, an expert of policing, from the Cambridge Centre for Evidence Based Policing.
• And he points out the difference between reactive and proactive data.
• Or to put it another way – the difference between people reporting crime and the police going out and actively looking for it.
• For example, those zero crime policies where police target neighbourhoods and clamp down on any and all violations in those zones, no matter how minor.
• So a location-based system like this could potentially be open to bias simply because police are already concentrating their efforts and attention on that particular area.
• In this instance, though the research team has admitted that the tool has the potential to be biased,
• Because of that it can be used to expose and overcome those biases.
• For example, they discovered in their analysis of the Chicago data that crimes committed in wealthy areas were more likely to result in arrests than crimes committed in poorer neighbourhoods.
• Which could potentially indicate that police devote more resources to solving crimes committed against richer residents.
Freda Liu: What would you like to end with?
Matt Armitage:
• We might as well stick with crime.
• This is the news that Ruja Ignatova, known as the Cryptoqueen, has been added to the FBI’s List of 10 most wanted fugitives.
• Ignatova is or was involved with a Bulgaria based proto-cryptocurrency called OneCoin that US prosecutors allege is at the centre of a $4bn fraud.
she disappeared from view in:• In the criminal probe into the company, a corporate lawyer called Mark Scott has already been found guilty by a Manhattan court of laundering $400m.
• OneCoin has been described as one of the biggest Ponzi schemes in history.
Freda Liu: What was OneCoin? A pump and dump scheme?
Matt Armitage:
• It seems it was far more elaborate.
• The coin itself was never launched.
• It used MLM techniques to sell its product, recruiting sellers and networks.
• Who sold, if I remember correctly, training courses, that came with tokens that could be converted into OneCoin when it launched.
• The entire story is quite incredible.
• There’s a great podcast called the Missing Crypto Queen that was produced by the BBC.
• It’s well worth a listen if you’re into true crime and or all things crypto and blockchain.
natova has been missing since:• The FBI puts people on its Most Wanted List when they believe the public can help to bring that person to justice.
• Which may suggest that she’s reseurfaced and that they have leads suggesting where she might be.
• So we might soon get a season 2 of the Missing Crypto Queen!