Dreamcatcher: Using AI to Analyze Dreams May Soon Be Reality

2020 has been a roaring disappointment for all of us, but that’s coming at it from more socio-cultural and global perspective. A lot of the world has been hampered by the Global pandemic, but on the plus side (if there is one) the tech world hasn’t slowed down much if at all when it has come to advancing what the digital world is capable of offering us. The just-around-the-corner advent of 5G is getting the bulk of the hype, but major advances in AI (artificial intelligence) really need to be receiving some fanfare too.

It’s fairly natural that 5G is going to be trumpeted most loudly by those of us who are a quality Canadian web hosting provider, and here at 4GoodHosting we fit the bill pretty nicely in that regard. When nearly everything you do is related to the workings of the Information Superhighway, it’s nearly impossible not to be wholly excited about what 5G has the potential to do for all of us. That’s likely why 5G has been a recurring theme in our content here, but today we can’t help but choose to go in an entirely different direction when it comes to be excited about something.

It’s always been interesting to us that a bad dream is known as a ‘nightmare’, but there’s no exact term used for a good dream. Thankfully, most of us have good dreams more often than we have bad dreams, but most of the time our dreams are of the ordinary, unexceptional, forgotten by the time we wake up type.

Sometimes, however, the dream we just had is something where we can’t get our minds off of it. Now imagine if there were a technological means of understanding what you can read into the dream you just had?

It may be a reality before long, and that’s because of Dreamcatcher

What’s All This?

Just a few months back researchers from Nokia Bell Labs in Cambridge, U.K. made the announcement that they’ve created a tool called ‘Dreamcatcher’ that is able to use the latest NLP (Natural Language Processing) algorithms to identify themes from dreams as they are reported by the people who’ve experienced them.

All of this is based on an approach to dream analysis called the continuity hypothesis. It’s then supported by strong evidence from decades of research into dreams, and the general consensus that suggests that a person’s dreams are reflections of their everyday concerns and ideas.

That might sound like a very elementary conclusion, but in truth it’s a different way of thinking about dreams than the deeply complex interpretations of Freud and Jung devotees who simply repeat what was taught to them in Uni, viewing dreams as windows into hidden desires and other very conceptual summaries on noted brain activity while asleep.

An Automatic Dream Analyzer

This dream analyzer A.I. tool works by parsing written description of dreams and then scoring them according to an established dream analysis inventory. That inventory is known as the Hall-Van De Castle scale.

It is made up of a set of scores that measure the extent to which different elements featured in the dream are more or less frequent than some normative values established by previous research on dreams. Taken into account are positive or negative emotions, aggressive interactions between characters, presence of imaginary characters, and other responses. What this means is that it is not an actual interpretation of the dream, and more about quantifying interesting or anomalous aspects in them.

Built on Existing Manual Data

Integral to building of Dreamcatcher were some 24 thousand dream report records from Dream Bank, the largest public collection of English language dream reports available. The algorithm they created based on them is capable of pulling these reports apart and reassembling them in a way that makes sense to the system.

By way of the person recording the dream and its content, Dreamcatcher is able to make assumptions based on thee description and automatically extracted various insights. The developers have stated that some of these insights are expected, while others are the furthest thing from what the connections they expected to make. One of the more interesting findings as they went through this process is that blind people’s dreams feature more imaginary characters than the norm. This suggests that our senses influence the way we dream.

Manual vs Digital Psychoanalysis

With this kind of analysis possibility, surely Dreamcatcher is something that psychology professionals are going to take an interest in. Whether or not they will, it is exciting to witness the growing ability of NLP to capture increasingly complex and intangible aspects of language and looking into the vast expanse of what might be capable with manual dream annotation.

So the question then becomes can an app or digital development match or exceed what these psychotherapy professionals are capable of when it comes to making sense of people’s dreams and helping them use their dreams to better their mental well being or life as a whole.

Some research has already been done on this, and when Dreamcatcher matched up to scores calculated by psychologists, the A.I. algorithm matched them 76% of the time

Keep an Eye on This One

It goes without saying that the potential of a mood-tracking app that asks users to record their dreams, and then pulls out recurrent though processes and deeply seated inclinations of spiritual shortcomings is pretty huge.

Yep, on-the-fly legit and implementable dream analysis would be huge! But in the bigger picture a kind of large-scale dream-tracking project that could map the world’s dreams onto real events to see how one informs the other may have even greater potential applications as it regards psychological and spiritual well being. Especially when combined and cross-referenced with other real-world data.

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