Computer AI makes sense of psychedelic trips

[rahli]

Artificial intelligence could help us better understand the effects of psychedelic drugs, by analysing narrative reports written by people who are using them.

Scientists barely understand how existing psychedelic drugs work to alter perception and intensify emotions, let alone keep pace with new ones flooding the market – often sold as "bath salts" or "herbal incense".

Enter artificial intelligence. Matthew Baggott of the University of Chicago and colleagues used machine-learning algorithms – a type of artificial intelligence that can learn about a given subject by analysing massive amounts of data – to examine 1000 reports uploaded to the website Erowid by people who had taken mind-altering drugs.

They found that the frequency with which certain words appeared could identify the drug taken with 51 per cent accuracy on average – compared with 10 per cent by chance. MDMA (ecstasy) usage was identified with an accuracy of 87 per cent.

The drug DMT (N,N-dimethyltryptamine) acts on the brain in different ways from the drug Salvia (Salvia divinorum), but the algorithms inferred that both elicit a similar response. This might be because both are typically smoked and so enter the bloodstream quickly, says Baggott. "Smoked psychedelic drugs may 'hit' people hard and fast in a similar way."

Baggott hopes the work will aid research into the effects of new and existing drugs. "You need to start with some theories about the effects of a drug," he says. "Machine learning can help us form those theories."

http://www.newscientist.com/article/dn21929-computer-ai-makes-sense-of-psychedelic-trips.html

[pete34]

rahli have you seen the website sciencedaily.com ?

it has all the science news from most publications

[rahli]

Yeah good one pete34. i just went and had a quick look and came across the psychedelic drugs section of the site - http://www.sciencedaily.com/news/mind_brain/psychedelic_drugs/

[whitewind]

Not trying to be funny but isn't this just data collecting and processing? Computers are good at that, they are a great tool, but it's hardly artificial intelligence. They are not discovering what a trip is - or what it means - just which words are used to generally describe a particular trip - by members of an online community who all share a similar language.

[rahli]

I guess so.

My friend tried DMT. He had no real background on DMT and was not expecting much from the trip. This is what he experienced -

The tv talking to him in an alien language. He was then sucked into a blackhole where he could see alternate wormhole dimensions where people where being ritually sacraficed by south american priests. This was with no preconseved ideas on what would happen.

The intensity and action of these drugs result in a fairly predictable experience and yes I guess all we have to explain this experience is english or which ever other language you have mastered.

I think the point of the study was so they can classify drugs by there response in users. All this study has told us is that these drugs are both entheogens inspiring an entheogenic reponse. Given the strenth and nature of this experience it is likely that folks will use similar words to attempt to explain what they have seen.

This method of drug classification could see some new upcoming designer drugs put into the entheogenic catagory of drugs without any prior ritual use, but based entirely on its reponse in users. This could be a good thing or a bad thing depending on the perseption of harm and benifit the community holds to certain classes of drugs and the future outcomes this perseption has on drug regulation.

[DELETED ACCOUNT]

I think the point of the study was so they can classify drugs by there response in users.

 

Yeah, that's what I got from the article too. I think that a classification model which maps between responses and drugs could be interesting to look into deeper, such as if there are any common chemical structures which may elicit similar effects. An understanding of this could lead to new drug discoveries, too... think PiHKAL/TiHKAL, the compounds in which were mostly structurally similar

I think the problem with the study is that those reports on Erowid are highly subjective, and you can't always put down what you feel into words, let alone in a consistent enough way to extract correlations with AI tools like machine learning... but it's a nice idea!

[rahli]

It would be interesting to survey the general populations words to describe the expected hallucinogen experience, assuming that the majority wouldn't have any first hand experience with hallucinogens and compare it to the actual experience. You could be almost sure that pink elephants would show up a heap of times in the general population but hardly ever in the actual experience.

[goneski]

Sounds like nothing more than data mining, and far from being machine intelligence.. Although a bit hard to say without reading the actual publication.

[rahli]

The original paper is attached in the following thread - https://www.dmt-nexus.me/forum/default.aspx?g=posts&t=33245