Human augmentation
The conclusion of my previous articles is that in order to leverage the collective intelligence of an organization, you need to create a highly connected network of teams made up of highly conscious individuals. The next question is how we can augment the capabilities of such a network, or in other words, how we can effectively integrate technology and data-enabled tools into complex networks of human collaboration to: (i) extract all gains from these advanced tools, and (ii) give more value-added and human roles to people in the organization, while reskilling them for these new roles.
To try to answer this question, we should first distinguish what we know from what we do not know regarding technology-enabled human augmentation. Although this is a complex problem, there are a few things we already know about it:
New technologies (AI in particular) will dramatically increase productivity in many (or most) jobs in the coming years. This will not be an immediate process because it will require not only the adoption of new technologies but also the transformation of job functions and business processes across organizations. But over time, it will have a major impact on the operating model of most companies, significantly raising their productivity.
This impact will not be limited -as we initially thought- to certain jobs more prone to automation (such as telephone operators or back-office assistants) but it will extend to many other roles, including functions that until recently we thought would hardly be impacted by AI tools. A good example is software development, as generative AI can deliver significant gains in developer productivity by automating tasks in functions like documenting code functionality, refactoring code or even writing new code.
This leap in productivity will upgrade many existing roles, demanding the upskilling of the employees who continue performing those (upgraded) jobs. At the same time, it will reduce the need for employees working in those functions, leaving millions unemployed and in need of reskilling to find a new job. In both cases, companies will have to make a relevant effort to upskill and reskill a large part of their workforce. Those companies able to make this effort earlier and faster will gain a valuable advantage over their competitors.
So far what we know. But let's also review what we do not know, so we can address it:
What upskilling will need those employees who continue developing their jobs, now using advanced technology tools? How can we promote it at scale?
What existing roles will grow in demand (and what new roles will emerge) because of this transformation, giving an opportunity to those who lost their jobs?
What skills will be needed to develop these growing or new roles? How can we promote this reskilling at scale?
Upskilling
The first opportunity to take advantage of new technology-enabled tools is upskilling. This is the case when technology is best used to augment workers in their jobs rather than replacing them. Upskilling will not only increase the productivity of workers so they can focus on more value added tasks, but it will also improve employee experience and happiness at work.
In any upskilling effort, learning to use new tools (e.g. LLMs like ChatGPT or Bard) is mandatory but it is not really the key element. Redesigning ways of working and operational processes will be much more relevant for upskilling to have a material impact on the business. For example, how the marketing team explores ideas for a new product campaign will become a different process in which the first step may now be to discuss prompting strategies to ask a generative AI model for ideas about possible product claims. Then, at a latter stage generative AI may also be used to generate personalized landing pages for different customer segments by creating dynamic content tailored to the specific needs of each segment, thus transforming the campaign launch process. All this means that the marketing team, beyond learning to use the new tools, will also have to learn to work in new ways following new processes.
Redesigning operational processes can have a big impact on the performance of any business or corporate function. Yet, you can still go deeper by using new technology tools to rethink business models or even identify new business opportunities. For example, GE Healthcare is using AI to develop new medical devices like AI-powered MRI systems that can produce higher quality images and reduce the scanning time for patients. The company is also using AI to develop new software for its medical devices, like AI-powered applications that can help clinicians to analyze medical images more accurately and to identify potential problems earlier.
For all these upskilling opportunities to be captured, the challenge is (as usual) change management. Implementing new business models may imply redesigning organizational structures, transforming business processes and redefining people roles, thus disrupting routines, creating uncertainty and leading to resistance. People may be concerned about the impact of change on their jobs, their relationships with their colleagues and their overall well-being. To overcome these challenges, sponsorship by top management and effective and transparent communication will become critical to gain employee buy-in and support.
Reskilling
But upskilling alone will not be enough. Millions of workers will require reskilling to be able to develop new roles after losing their jobs. The question then is what existing roles will grow in demand as part of this transformation, giving an opportunity to those who found themselves unemployed.
To answer this question, we may analyze what human skills will be more difficult to replace by AI tools. If we look at the theory of multiple intelligences (eight in total) proposed by psychologist Howard Gardner, we can select the following four skills:
Bodily-kinesthetic intelligence: coordination of body motions and capacity to handle objects skillfully. Despite all recent progress in AI, robots still struggle to perform tasks requiring high manual dexterity.
Naturalistic intelligence: sensitive, ethical and holistic understanding of the world and its complexities, including the role of humanity within the greater ecosphere.
Interpersonal intelligence: sensitivity to others' moods, feelings, temperaments and motivations (empathy and compassion) and ability to cooperate as part of a group.
Intrapersonal intelligence: ability to understand oneself, including one's emotions, thoughts, motivations and values, and to use this understanding to make decisions and communicate effectively.
We can synthesize these intelligences in three types of skills: our embodiment (the way that our body and mind are interconnected and influence each other), our capacity to meaningfully connect with others (people and nature) and our capacity to truly connect with ourselves (our emotions, thoughts, motivations, purpose in life…). If those human skills are the most difficult to replace by AI, what existing jobs will be most in demand as they require those skills?
From an industry standpoint, one can anticipate that jobs in sectors like healthcare and education will gain weight in the global workforce. Healthcare professionals need to build rapport with their patients, understand their physical and emotional needs and provide care in a compassionate way. Similarly, teachers of all grades and subjects need to build relationships with their students, understand their individual needs and create engaging and effective learning experiences. Both healthcare and education professionals also need to use their bodies to effectively communicate non-verbally and to create a safe and supportive environment.
Beyond these sectors, one can also foresee that some roles needed in virtually every industry will also gain weight. Here are some examples:
Salespeople, who need to build relationships with potential customers, understand their customers' needs and present their products or services in a way that is persuasive and engaging.
Product managers (responsible for the overall success of a product from its conception to its launch and beyond), who typically need to have excellent interpersonal skills as they have to work closely with cross-functional teams including design, engineering, marketing and sales.
Solutions architects (responsible for designing and implementing technical solutions that meet business needs), who have to bridge the gap between business and engineering teams by showing strong communication and interpersonal skills, in addition to a deep understanding of a variety of technologies.
Recruiting consultants, who need to be able to listen actively to their clients and candidates in order to understand their needs and motivations, as well as to build solid relationships with them by being empathetic and trustworthy.
Coaches of different types (executive coaches, team coaches, agile coaches, etc) who need to build trust relationships with their clients, understand their goals and challenges and provide guidance and support from a state of inner peace.
Finally, the upcoming technological revolution will not only rebalance the weight of existing roles in the overall economy, but will also lead to the emergence of new roles that we cannot yet imagine. Just as 15 years ago no one could have envisioned the relevance that social networks would end up having in our economy and our society, it is very likely that new technology-enabled concepts that we are not yet able to imagine will have a big impact on the economy and workforce in the coming decades. But even when we do not know what new roles may eventually emerge, we can bet that skills such as the ones mentioned above (embodiment, interpersonal intelligence and intrapersonal intelligence) will play a relevant role in developing these new roles.
A company-wide effort
Both upskilling and reskilling will require a company-wide effort that needs to be sponsored by the top management and clearly and openly communicated to the entire organization. For such an effort to work, two approaches should be followed:
i) Centralized architecture, decentralized execution
The strategy here is to follow a structured and coordinated approach to implementing upskilling and reskilling initiatives, while empowering individual units to make decisions and take action within their specific areas of expertise. This approach combines the benefits of ensuring that efforts are aligned with organizational goals and strategies (so that individual units are not constantly reinventing the wheel) with the flexibility and agility of a decentralized execution.
For example, an organization may centrally decide that all business units should upskill their customer service teams to leverage a new corporate platform that integrates AI tools from different partners, while leaving each business unit the flexibility to decide which processes should be redesigned and when to do it depending on the dynamics of each business unit.
ii) Start small, learn fast and scale up
The approach in this case is adopting a methodology that emphasizes incremental change, continuous learning and adaptability, in contrast with large-scale, top-down programs that can be risky and slow to yield results. By breaking down upskilling and reskilling efforts into manageable phases, the organization will be able to experiment, gather feedback and refine its skilling strategies before committing to a broader implementation. This iterative approach reduces the risk of failure and enables the organization to learn from its mistakes and adapt to changing circumstances.
Following the previous example, rather than asking all business units to launch their upskilling initiatives simultaneously, you may decide to start with a single business unit (start small). This way, the implementation can be done faster and you can learn from your mistakes and adapt the program as needed (learn fast) before taking it to all other business units (scale up).
Beyond these approaches, it is important to understand that this type of transformations requires patience and perseverance to succeed, as changing the culture of a company -which is what we are ultimately trying to do- is always a long and complex process.
Conclusion
In summary, after the series of articles that I have published here, we can conclude that in order to leverage the augmented collective intelligence of an organization, you have to create:
An organization based on a network of autonomous and interconnected teams that results in an effective system of communication, interaction and decision-making at scale, facilitating the spread of information across the organization and making it more resilient to disruptions.
Autonomous teams that are made up of highly conscious individuals who have been able to develop self-awareness (knowing who they are) and systemic vision (understanding the world as a system), thus gaining the capacity to effectively collaborate with each other and truly pursue collective goals.
Highly conscious individuals who leverage new technology-enabled tools to rethink their business models and redesign operational processes (upskilling) while focusing their work on value-added activities demanding human skills like embodiment and interpersonal and intrapersonal intelligence (reskilling).
Ricardo check this use of collective intelligence out.
Lots of people pointing out problems. Anyone discussing peaceful solutions?
For the past two years we have been trying to find solutions to our biggest problem: THE CORRUPTION OF THE SYSTEMS THAT GOVERN OUR LIVES.
Is it solvable? Yes of course. All problems that do not defy the laws of physics are solvable.
This took us 2 years to write this. How to fix corrupt government in 3 simple steps:
https://open.substack.com/pub/joshketry/p/how-to-fix-corrupt-government-in?r=7oa9d&utm_medium=ios&utm_campaign=post