Innovation advisory for organizations engaged in environmental and social transformation, so they can harness the power of AI-augmented collective intelligence.
AI that works at work. In organizations, for people. Through AI-augmented Collective Intelligence (ACI).
While the initial use of geospatial #AI driven Augmented Reality like what Google just announced with Maps (starting with Paris and Singapore) is going to be aimed at marketing and sales, imagine the possibilities when the creation tools will be given to millions of “citizen creators” who can build their experiences for their own neighborhood.
#GenerativeAI is able to support #innovation processes more than ever before. But what you get out of the box is limited - just like what you get in a workshop with smart people without a good facilitator.
To see what can be done by guiding users and machines to collectively create, try AIdea Collider, a GPT built on OpenAI ChatGPT, which is now becoming available to all ChatGPT users (link in the comments).
You can also try similarly structured ones, like Jeremy Utley Idea Collider or Ethan Mollick Innovator - all GPTs.
AI that works at work. In organizations, for people. Through AI-augmented Collective Intelligence (ACI).
Innovation very often comes from recombining adjacent ideas. Unfortunately, our search engines for knowledge don't typically show ideas adjacencies - or if they do, they do that as a black box that discourages deliberate exploration.
That's why I believe that in the future, we will have increasingly better knowledge exploration through the mining of knowledge graphs facilitated by AI.
This example from BCG Henderson Institute (Idea Explorer) is interesting - they use the corpus leadership publications to enable the reader to discover following a more interesting path than just a bunch of links. Imagine what you could do when you applied some of the same principles to the entire knowledge that is publicly accessible. You could access - and engage with - our #collectiveintelligence.
AI that works at work. In organizations, for people. Through AI-augmented Collective Intelligence (ACI).
Happy Earth Day.
For a reminder of how Earth functions as a collectively intelligent system, have a look at the studies below. It is just extraordinary - insightful, humbling, inspiring.
And a reminder that our technology can help Earth function better - not just worse. Think of monitoring, modeling, and pricing of externalities in our markets. H/T Rafael Kaufmann Nedal, whose work in this space should be of interest to some.
AI that works at work. In organizations, for people. Through AI-augmented Collective Intelligence (ACI).
This (link in the comments) is an insightful read from Ajay Agrawal and colleagues. It argues that the “Turing trap” debate of obsession with #AI (and other information technology) automation at the expense of work on augmentation, and its implication on inequality, misses some key aspects.
“One person’s automation is someone else’s augmentation”, for instance when talking about doctors’ diagnoses which, if partially automated, could become easier to unbundle from (scarce, expensive) doctors and accessible to (somewhat more available) nurses.
The implication is that designing for automation of certain tasks could result in a more widespread positive impact than initially thought. They call it Turing Transformation.
At the #CollectiveIntelligence level, the net effect of these technologies is still an augmentation one.
AI that works at work. In organizations, for people. Through AI-augmented Collective Intelligence (ACI).
What are the use cases for #AI (predictive and generative) in specific processes? That's a critical question that many ask themselves these days when they try to apply it. Remarkably, I didn't find a tool to help do that - so I created Apta, a simple OpenAI GPT, shaped its collaborative workflow so it asks you questions before giving answers and fed it with examples.
Try it for yourself - the link is in the comments. You will need a ChatGPT Plus account. This is just a simple prototype, inspired by the work we do at MIT's Center for Collective Intelligence: imagine what could be done with more concerted work.
Gemini for scientific knowledge is one of the things I was looking forward to when I wrote, about 14 months ago, the essay “If the world knew what the world knows” (link below). Then Perplexity happened. Then this. The burden of knowledge may be lightened. And the cross-discipline recombination that MITs Buheler demonstrated is also exciting. Of Gemini one can intuit an ecosystem that makes it more useful to specific types of users. One more thing to look forward to in 2024! https://lnkd.in/ePwxdhaP
Great vision. And great to see that the work we did at #genpact over the years is recognized as a future-oriented exemplar of skill building leveraging an #AI augmented #collectiveintelligence architecture. Lots still can be done, lots of potential. Piyush Mehta Shalini Modi Prashant Shukla Rajlakshmi Saikia Kunal Dureja Tiger Tyagarajan
Are we on the edge of a new category of HR jobs: AI work engineers?
Ryan Roslansky the CEO of LinkedIn published yesterday an interesting article in Harvard Business Review on Talent Management in the Age of AI.
In the article he made a prediction of an entirely new category of jobs centered around the idea of “AI transformation,” where teams are tasked with figuring out which AI tools are the right tools to grow the business and identify as a result the right workforce strategies to keep business teams agile and engaged. As LinkedIn CEO he expects the battle for talent in those roles to be fierce and already begun.
It’s clear that companies who use AI to automate their operations solely to reduce employee numbers will only achieve short-term productivity gains. There is a risk that re-thinking and re-engineering work as a result of AI will mean going back to the era of time and motion studies of the late nineteenth and early twentieth century. In other words a modern form of so-called scientific management to identify what part of the process can be “AI’ed” with the risk of making humans even more a cog in the (information)machine.
To truly capture the full business benefits of Generative AI we need to start with human engagement, agility and business value as Ryan Roslansky points out and engineer the AI solution in collaboration with the source that in the end makes the difference: humans.
https://lnkd.in/ePurNbUH
This is a great analysis. And one more point:
With the new AI, new jobs will probably be aplenty, as long as new use cases are found (and they are being found).
BUT - not with the same skills! If all you could do when Excel was introduced was do math by hand, you had to build new skills. We must give our teams guidance on the "expansion path" that they can follow to move to new roles, and the skills required, and provide them with the learning infrastructure to get there. Failing that, lots of anxiety will persist, and generate unrest in our organizations and societies.
Thanks, Nico Orie for the analysis and tee-up.
Worried AI will take your job? The history of Excel should give you hope.
In 1979 Dan Bricklin invented VisiCalc, the first spreadsheet program with a modern interface running on the Apple II and an immediate business sensation. VisiCalc was followed by Lotus 1-2-3 mid 80’s and later by Microsoft Excel.
The launch of modern spreadsheet programs had a transformational impact on many businesses. It co-enabled for instance the growth of the Private Equity (PE) industry, since cash flows vs. debt payments could be easily monitored, and a formerly complex net present value calculation now just involved a formula for a cell.
Over the years the dependency and risk of excel sheets also grew with the most famous example being JP Morgan losing $6bn, in part because a risk indicator in a spreadsheet was being divided not by an average of two numbers but by their sum - making the risks look half as big as they should have done.
Spreadsheets also transformed the jobs in Finance departments.
Interesting question is if there are parallels between the impact of the introduction of modern spreadsheet programs and the upcoming wave in AI that according to some will come after our jobs.
Morgan Stanley did an interesting study into the impact of excel. They found that after the introduction of Microsoft Excel in 1987, there was a reduction in the number of Americans working as bookkeepers and accounting/auditing clerks (from ~2 million in 1987 to just above 1.5 million by 2000) — but there was also a significant increase in Americans employed as accountants/auditors (rising from ~1.3 million in 1987 to ~1.5 million in 2000) and management analysts & financial managers (from ~0.6 million in 1987 to ~1.5 million in 2000)".
In other words, any decline in one type of job was more than offset by the creation of new, adjacent jobs.
It’s likely AI will show a similar pattern. Technology doesn't usually take jobs wholesale - it chisels away the easily automated chunks, leaving humans to adapt to the rest.
Source: https://lnkd.in/e7nJctC4
