Collective Intelligence (CI) and AI powering Thoughtz ($THZ)
Till now, AI has been viewed as an alternate to do the tasks that can be made more efficient through analysis or prediction therefore, automating them and reducing the need of humans to do them. It has always taken either of the two stances: AI boon or bane. It is either a technology that is killing jobs, replacing humans to do simple tasks or the one curing diseases and dealing with the climate crisis. Little attention has been given to the ability of humans and AI thinking and working together, thereby identifying problems, developing solutions and making decisions. AI can be considered a citizen science, amplifying the digital democracy and therefore, shaping a future of minds and machines to harness collective intelligence.
Before going any further with the discussion, it is important to understand in simple terms what exactly is meant by collective intelligence- collective intelligence is the capacity of humans and technology to work together, to mobilise a wide range of ideas, information and insights. It has been around for a long-time, Wikipedia is popular example of the same.
Collective Intelligence offers four distinct opportunities to help decision-makers and communities solve problems:
1. Understand problems
2. Seek solutions
3. Decide and act
4. Learn and adapt
Collective Intelligence can be broadly used to bring people and/or data together. Therefore, the core methods of CI can be broadly described in three ways:
1. Connecting people with people: when people work together in groups, they create intelligence that can not exist on an individual level. Making decisions as group, forming consensus, sourcing ideas from different backgrounds, cultures and thought processes, and motivating people to do better are all a part of CI. It can be done via open ideation, peer production etc.
2. Connecting people with data: it brings data and people together via categorizing, filtering data such as audio or photos. It goes beyond data gathering and can include analysis, evaluation etc. For example, CI can be harnessed via social media. LinkedIn, Facebook etc are popular apps for identifying the patterns and trends that interest the users and can go a long way in ensuring success of one’s business. Pinterest is a popular app to see what would sell, simply by uploading a photo on Pinterest and if it is viewed or pinned by the users, it can speak volume about the things that would sell.
3. Connecting data with data: it brings together diverse data sets to help generate new and deeper insights, it can be done using the data provided by users on social media, mobile phone geolocation, etc.
Collective Intelligence today has helped unravel solutions to most of the complex problems of the world like land degradation, co-ordinating aid during emergency response, global climate change, value co-creation in the public sector etc. In these situations, it is the ability of AI to find patterns in the big data sets is useful to streamline decisions. Though decisions are ultimately made through group deliberation about competing values, trade-offs and priorities, but it is the technology that enables decision-makers to engage in such complex problems in the first place.
Bringing together these two fields is not easy and has its own drawbacks, like in cases of healthcare epidemics or extreme weather events where there is no precedent, there is no guarantee that the model would be accurate. When it comes to these decisions making, this inaccuracy can be dangerous. In these situations, the human ability to understand the conditions, update knowledge database and react as per the need of the hour, human abilities fill the gap of machines. It is also not easy to develop an absolute intelligence quote for
machines. This entire effort of CI involves a big trust on the ability of AI to make sense of the data, which of-course doesn’t discount the chances of errors. Humans and machines work together but only after machines have some precedents or rules set to follow suit, therefore, any errors made in setting the rules for exchanging information and skills can increase the
chances of inaccuracy in predictions.
Although there are drawbacks, it is beyond necessary to make the most of the CI opportunity. This can be essentially helpful if the data set used is diverse, as it would improve the cognitive ability and there would be space for vital creativity and learning in the teams.
‘Wisdom of crowds’ is in-fact one of the basic principles that CI relies upon, which means that the mistakes made by everyone are slightly different and if one person overestimates, the other one would underestimate and their mistakes would cancel out each other’s errors. Another core principle is inviting and appreciating participation from everyone via ensuring the end goal has some benefit for every participant, thereby motivating them to think more.
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