“Those that partnered AI with human personnel achieved the greatest results by enhancing each other’s strengths—human leadership and creativity coupled with AI’s quantitative power and speed.”
If you’re fretting about artificial intelligence’s purported threat to how humans work together, be sure to raise the issue during your next Powerpoint presentation or email composition.
If you get the implicit irony in that suggestion, you can follow it by treating yourself to an enormous sigh of relief.
For those still puzzled, the kicker is that Powerpoint incorporates many elements of machine learning and AI engine. Powerpoint and other regularly used software tools (think Adobe, and various apps on you on your mobile devices) use AI algorithms to select templates, images and other materials, saving time while not losing focus on a presentation’s primary themes.
That example also illustrates one of the many potential benefits as machine language and AI assumes an ever-growing role in the way humans collaborate with one another—even to the point of reinventing and improving the very nature of collaboration.
This isn’t simply a matter of people collaborating with AI (although that’s a significant topic unto itself.) It’s the inherent possibilities of people leveraging artificial intelligence to better collaborate with other human beings.
It’s time for us to reset.
Cross-Boundary Collaboration Defined
If, as many authorities are telling us, collaboration is growing ever more critical to work and society, cross-boundary collaboration stands as an even greater tipping point between those who succeed with innovation and others who struggle to keep up.
Whether we recognize it or not, collaboration is growing ever more critical to work and society. As Texas A&M University Human Resource Development professor Michael Beyerlein pointed out, the essential value of collaboration incorporates three primary driving factors:
- Group intelligence. As challenges and problems become increasingly complex, so too does the significance of multiple stakeholders pooling their strengths to devise viable solutions.
- Learning. Whether at home or on the job, humans are charged with learning faster, more comprehensively and from a growing number of sources.
- Goal alignment. By positioning objectives as complementary rather than competitive, common benefits can be achieved instead of succeeding at someone or something else’s expense. Greater benefit for all is the result.
In short, we are very much all in this together. And, in an environment characterized by exponential change that’s only taking hold at an accelerating rate, our capacity to unite and work as one will prove critical to leveraging that change rather than struggling with it.
Cross-boundary collaboration might be viewed as conventional collaboration that’s taken further. Defined simply, cross-boundary collaboration defines an environment in which ideas are genuinely celebrated—all suggestions and ideas are welcomed. So, too, is the source of that input broad and varied–anyone is invited to contribute, regardless of their position or group, both within and outside an organization.
It doesn’t take a great deal of imagination to see that’s the sort of setting where innovation flourishes—the sort of game changing ideas and vision that can transform entire organizations and even industries. Even more important, it’s a setting where sustained innovation takes place—the capacity to replicate the innovation process over and over, consistently producing viable, exciting results.
The Role of Personas
Effective cross-boundary collaboration doesn’t hinge just on a welcoming environment, however important that might be. A diversity of input is equally critical—an array of perspectives, ideas and vision contributed by a variety of different people and sources.
Successful innovation depends upon input from a wide range of people in collaboration, sharing ideas, comparing observations, offering wide-ranging perspectives from their diverse viewpoints, and brainstorming solutions to complex problems. We refer to these divergent perspectives as personas. Here are a few examples, as we defined them in our previous work innovation:
- Learning personas — keep an enterprise from being too internally focused and caught in their comfort zone.
- Organizing personas — move the innovation lifecycle forward; they are skilled at navigating processes, politics, and red tape to bring an innovation to market.
- Building personas are closest to the innovative action, establishing connections between the learning and organizing personas; they apply insights from the learning personas and channel empowerment from the organizing personas to facilitate innovation.
As you can see, the greater the number and variety of personas, the more productive and rewarding the overall process. And, equally obvious, is the potential caveat of limitations. The fewer the participating personas, the less the potential for compelling innovation.
AI Steps Into the Collaborative Breach
The solution, boiled down, is relatively straightforward. Need more or different personas to help drive cross-collaborative innovation? AI could be significant value-add.
AI-generated personas can be seen as digital “characters” or “personas” that can effectively augment/replicate a human persona. While these can be used in a variety of applications, including research, design, strategy, and other tasks, personas can also participate in cross-boundary collaboration, effectively adding fresh observations and analysis to the overall conversation.
One powerful advantage to AI personas is the breadth of their DNA, as it were. AI personas can be based on a broad swath of demographic factors, industry data, market research and other information. While human personas may be rather limited as to the source of their input, AI personas have the inherent capacity to be much more broadly grounded.
The process with which an AI persona is used can be similarly straightforward. After introducing input from others involved in cross-boundary discussion and examination, AI can quickly examine all the material in play to offer additional analysis and exploration.
Like other usage of AI, the advantage to AI-generated personas is speed. AI review and analysis can take place in a fraction of time required by its human counterparts. In a shifting environment where things are changing more often and faster than ever before, the capacity for quick, accurate analysis can prove a powerful ace in the hole.
Although concerns about bias are genuine and need to be addressed, AI nonetheless can prove an effective tool in arriving at decisions and solutions in a highly empirical manner. That information, in effect, can make humans better cross-collaborators—more informed, with higher quality data and other material with which to work together with others. That leads to better human-driven outcomes.
Even better, AI-generated personas are not cast in stone. Once created, the AI persona can be revised and retrained as new data and insights emerge. This ensures that the persona’s input and participation remain aligned with shifting market conditions, organizational goals and other elements that are subject to change.
Humans are No Less Important
It’s helpful to bear in mind that he purported “threat” of AI taking control rather than collaborating is hardly new—particularly in popular culture. Frankenstein was published in 1818. Roughly a century later, a Czech play titled R.U.R. (Rossumovi Univerzální Roboti) portrayed robots rebelling and slaughtering most of their human “masters”. And on up through 2001: A Space Odyssey’s Hal (“What are you doing, Dave?”), Transformers—here robots are divided among do-gooders and n’er do wells—up to more positive castings, such as the ever helpful J.A.R.V.I.S. which serves as Tony Stark’s invaluable right hand man in the Iron Man movie series.
Although the topic of AI as a whole can still drive many people to reach for a paper bag in which to breathe, AI-generated personas are not geared to replacing human participants. Rather, they’re in place to augment and strengthen the entire process. While AI can be fast and empirical, empathy is simply a factor that—so far—cannot be inputted into the guts of AI. That, happily, remains the sole purview of human beings, which is what makes the AI/human cross-collaborative process both balanced and potentially very prolific.
Moreover, everything simply seems to function that much better when humans and AI collaborate. According to comprehensive research by Accenture involving some 1,500 companies, researchers determined that companies using AI to effectively replace human workers only reaped short-term benefits. On the other hand, those that partnered AI with human personnel achieved the greatest results by enhancing each other’s strengths—human leadership and creativity coupled with AI’s quantitative power and speed.[1]
It’s becoming increasingly clear that innovation is not a take it or leave it option–it’s essential for any enterprise moving forward. Cross-boundary collaborative teams, working with enabling technologies such as AI-generated personas, can power meaningful, sustained innovation.
Copyright (c) 2023 by Faisal Hoque. All rights reserved.
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[1] Daugherty, Paul, Wilson, H. James, “Collaborative Intelligence; Humans and AI are Joining Forces,” Harvard Business Review, July-August 2018.
