Can generative AI help build a global hive mind?

On the earth of science fiction, the notion that humanity will in the future join our brains collectively into a world “hive thoughts” dates again to a 1930 novel entitled “Final and First Males” by Olaf Stapledon. It recounts a fictional “future historical past” during which humanity evolves biologically right into a species that may hyperlink telepathically and kind collective minds of maximum intelligence.

In the true world this pursuit is known as Collective Superintelligence, and it’ll not require telepathy or different fictional gadgets. As a substitute, it can use rising generative AI applied sciences to attach giant human teams into real-time deliberative methods, enabling us to solve difficult problems by harnessing our mixed data, knowledge and perception in highly effective new methods.

This pursuit has been my private focus as an AI researcher for the final decade and I consider it has the potential to supply superintelligent systems that keep human values, morals and pursuits on the core of each perception, evaluation or resolution. After all, for many individuals the thought of enormous human teams pondering collectively in real-time methods appears unnatural, and even creepy, however mom nature would disagree.

In reality, many social species have advanced naturally on this course, creating the power to make fast selections in giant teams that enormously exceed the brainpower of particular person members. Biologists name this Swarm Intelligence, and it allows faculties of fish, swarms of bees and flocks of birds to rapidly remedy life-and-death issues at intelligence ranges that far exceed the psychological capability of their particular person minds.

One exceptional type of Swarm Intelligence that impressed my very own academic research during the last decade is the standard fish faculty. Though it seems to be easy on the floor, the underlying dynamics allow hundreds of members to make complicated selections with no particular person in cost. In reality, fish faculties could make good selections even when no single member has adequate data to handle the issue at hand. Take into account the picture under: 

The fish faculty above faces a hypothetical drawback of maximum significance: Three predators strategy from three completely different instructions. In the meanwhile proven, no particular person is conscious of all three threats. In reality, most aren’t conscious of any threats. There’s a small group of fish within the higher left that’s conscious of the primary predator, a small group within the decrease left that’s conscious of the second predator, and a small group within the higher proper that’s conscious of the third predator. A lot of the different fish are unaware of the hazards.

So, how can this huge group, during which each member has restricted data (and no members possess all the knowledge) remedy this life and loss of life drawback and rapidly transfer in the best course? The very first thing to know is that fish have a particular organ on the edges of their physique referred to as the lateral line that permits them to trace the pace and course of neighboring fish primarily based on stress and vibrations within the water round them. Utilizing this organ, they will understand the intent of their neighbors (that’s, the pace and course that these fish consider the college ought to go). This communication is bidirectional so we are able to consider it as a local deliberation during which small teams determine on the movement of their small portion of the college.

That is fascinating, however it doesn’t clarify how international selections are made. In spite of everything, the group on the best that sees a predator approaching, doubtless decides the college ought to transfer left. On the identical time, the 2 teams on the left doubtless determine the college ought to transfer proper. And, teams within the center, which don’t have any data of the predators, are prone to maintain transferring within the course they had been already going. So, how does this get resolved right into a single fast resolution that evades the pressing threats?

The magic occurs as a result of each fish within the faculty “deliberates” with a distinct group of close by neighbors. This implies there are various “overlapping conversations” occurring directly which allows data to rapidly propagate throughout the total faculty. As proven under, the result’s a swift and decisive collective answer to the issue.

On this approach, education fish could make rapid and effective decisions throughout giant populations, even when all members have restricted data. Such a ability could be much more highly effective for giant human teams.  In spite of everything, the issues confronted by teams of individuals are considerably extra complicated and contain much more views. This begs the query: May giant human teams deliberate in real-time with the effectivity of fish faculties and rapidly attain optimized selections?

For years this objective appeared not possible. That’s as a result of human conversations have been proven to be most efficient in small groups of four to seven folks and rapidly degrade as teams develop bigger. It is because the “airtime per individual” will get progressively squeezed and the wait-time to answer others steadily will increase. By 12 to fifteen folks, the conversational dynamics change from considerate debate to a sequence of monologues that develop into more and more disjointed. By 20 folks, the dialog ceases to be a dialog in any respect. This drawback appeared impenetrable till advances in generative AI opened up new options.

The ensuing expertise is known as Conversational Swarm Intelligence (CSI) and it guarantees to permit teams of doubtless any measurement (200, 2000 and even 2 million folks) to debate complicated issues in real-time and rapidly converge on options with considerably amplified intelligence. Step one is to divide the inhabitants into small subgroups, every sized for considerate dialog. For instance, a 1,000-person group might be divided into 200 subgroups of 5, every routed into their very own chat room or video conferencing session. After all, this doesn’t create a single unified dialog — it creates 200 parallel conversations.   

As described above, fish faculties remedy this drawback by having native teams overlap, permitting data to rapidly propagate throughout the total inhabitants. Sadly, we people didn’t evolve with the power to be in a number of conversations directly. In reality, if we strive to concentrate to 2 conversations, we instantly get confused and might’t deal with both. That is generally referred to as the “cocktail party problem” as a result of it occurs typically when small teams collect inside earshot of one another. For those who strive to concentrate to a neighboring dialog you instantly lose observe of the dialogue you might be in. 

So how can we overcome this human limitation?

CSI expertise solves this drawback by inserting LLM-powered “conversational surrogates” into every subgroup. These AI brokers are tasked with distilling the real-time human insights inside its assigned group and sharing these insights with surrogate brokers in a number of different teams. The receiving brokers specific the obtained insights in their very own teams as pure first-person dialog. On this approach, every subgroup is given a synthetic member that participates seamlessly in overlapping conversations, guaranteeing data freely propagates throughout the total inhabitants. 

Quite a lot of latest research counsel the strategy is efficient. For instance, a 2023 study performed at Carnegie Mellon College to check real-time deliberations amongst roughly 50 folks in conventional chatrooms versus conversational swarms. When utilizing the CSI construction, teams had been capable of maintain extra coherent conversations that rapidly converged on options. As well as, every particular person was discovered to contribute 50% extra content material (on common) than contributors utilizing conventional strategies.

However does this amplify group intelligence?

To discover this, a follow-up 2024 study by researchers at Carnegie Mellon and Unanimous AI examined the power of networked human teams to take IQ exams as a real-time “hive thoughts.” Outcomes confirmed that teams of 35 individuals who averaged an IQ of 100 (the fiftieth percentile), may rating an efficient IQ of 128 (the 97th percentile) when utilizing an internet CSI platform referred to as Thinkscape. Though this examine used conversational teams of solely 35 contributors, different latest research have examined teams up to 250 with success.

Whereas the above research used textual content conversations, the core strategies of CSI might be deployed for teleconferencing, videoconferencing and even VR conferences, enabling giant teams of a whole lot and even hundreds of members to carry coherent real-time conversations that effectively remedy issues, prioritize choices, brainstorm concepts and attain selections, all with amplified group intelligence. This has the potential to reinforce a variety of fields from enterprise collaboration and market research to civic engagement and deliberative democracy. 

In the long run, this strategy might be used to construct superintelligent methods which might be inherently aligned with human values, morals, knowledge and sensibilities. In concept, we may use CSI expertise to allow hundreds of thousands of people all over the world to “assume collectively” as a world brain-of-brains to unravel our most tough issues. For me, this can be a safer path than counting on a purely synthetic superintelligence, as AI methods might not keep human values or pursuits over time. That’s why I consider we want applied sciences like Conversational Swarm Intelligence and instruments like Thinkscape that leverage gen AI — however maintain people within the loop. 

Louis Rosenberg is a longtime researcher within the fields of AI, collective intelligence and combined actuality. He’s CEO and chief scientist of Unanimous AI.