“You say you want a revolution”
It is truly an era of discontinuity. Old models of institutional education, traditional teachers, conventional guidance and pathways to opportunity are crumbling. Moreover, they are unequal. Elite institutions are able to offer their constituents disproportionate benefits while those who do not have access to them due to location, financial resources or social status cannot obtain the “golden tickets”. and have to settle for a seat at the back of the crowd.
In the legacy model of human potential described earlier in Part II of this series, a variety of human intermediaries have traditionally served to bridge the yawning gap between the supply of talent and the demand for opportunity. Call them human resources professionals, guidance counsellors, teachers, parents, friends. The sheer complexity of the employment landscape, the disorganized nature of the educational landscape, the inefficiency with which talent tries to find relevant opportunities suggests that human approaches alone are insufficient. What is likely to emerge are new hybrid models that use both human contact and data science.
A number of promising technological innovations are beginning to bridge the missing link that separates talent from opportunity, students from employers, citizens from goals. However, such innovations have so far advanced the cause in piecemeal fashion, fueled by the narrow interests of profit-seeking investors. What is needed now is a new kind of critical mass of innovation and new funding models that will drive the culture of human capital at scale and incorporate the following features:
PERSONAL DIGITAL IDENTITY
A meaningful approach to personal digital identity is emerging from a portfolio of innovations that put the individual — not an institution — in control of their data and the privacy that protects it. This includes the traditional “report card” types of information, but
will eventually support a much larger web of self-representation that demonstrates accomplishment, character, and potential. Additionally, new digital identity technology will serve as portals to access a wide range of services in areas such as personal finance, wellness planning and more.
Personal digital identity is important precisely because it is personal, as it allows for a high degree of personalization and adaptation. This is important because learning assets are increasingly available in the public “distributed space”, whether derived from a curriculum module developed at a particular institution, from the work of an independent teacher publishing his or her online work, NGOs, employers, etc. in the shared space is a growing, albeit disorganized, soup of learning assets that are ripe for repurposing and reshaping. Which leads to…
Orchestration technology is necessary to find the best solution for each end user and each use case. The traditional monolithic learning model in which learning assets are embedded in semester-long multi-unit courses that offer no customization is becoming obsolete. New ways to apply resources that are personalized and relevant to a specific person’s passions and career goals are now on the verge of becoming a reality.
NEW LEARNING ASSETS
We’re starting to see efforts to atomize learning assets so they can be searched and recontextualized by AI algorithms, a process that capitalizes on AI’s ability to analyze large amounts of information and make sense of them in a highly personalized way for a given end user. And as content becomes increasingly atomized and searchable, it will include some version of a “smart” metadata layer that controls access, consent, and usability on its own.
The growing flow of modular learning assets in public space is a striking example of disinter-remediation. A four-year university experience will become less
attractive to many, when a variety of intermediaries, enabled by technology, will be able to compose learning experiences tailored to the content requirements, learning style and professional passions of a particular end user. The technology will do for standardized educational content what CRISPR does for DNA sequences – atomizing key elements to put them back together in more relevant and personalized ways. Entrepreneurs will generate such orchestration capabilities through a variety of approaches to building increasingly intelligent, data science-driven platforms. Consider this an example of dis-inter-mediation!
USER EXPERIENCE DESIGN
Innovation also occurs in the development of new levels of user experience. Virtual reality/augmented reality and emerging metaverse approaches will increase the impact and “production value” of digital experiences. Digital twin technology will allow each person to interact with a digital representation of themselves, including an ideal virtual “me” that creates an ambitious horizon in which to navigate. This digital twin technology can also serve as an interactive medium for an individual to compare their achievements, establish learning plans, track performance, create accountability, and more. And with the rapid advance of NLP (natural language processing), interaction with a digital twin
will become increasingly conversational and highly personalized for that individual. These innovations will enable new forms of virtual mentoring, career counseling and even therapy.
Of course, this also implies the need for a high level of transparency and trust in our interactions with technology. We will need a new level of AI ethics in the design of these systems that is not beholden to special interests, but is just and ecumenical. We need regimes that protect privacy and ensure individual ownership of data.
When it comes to human collaboration with AI, we will need to develop new rules of engagement. A human will always need to be aware of high-critical decisions such as seeking surgery for a medical condition or a drastic career change. However, human-AI collaboration for routine and less-critical decisions is a force multiplier for “human-like” services, which can become more efficient and accountable, enabling empowerment. ladder.
In short, what is presented here is a vision of the culture of human capital that disrupts traditional institutional models. The culture of human capital will no longer be subject to the tyranny of established organizations. Instead, a new digital framework will make life planning, learning planning, learning assets, and demand-side opportunities accessible to everyone. A new dynamic will emerge in which employers reach out to promising candidates and offer them personalized learning paths and opportunities. Individuals on the talent side will increasingly abandon traditional four-year college and graduate programs for self-directed, modular approaches to ingesting knowledge that relates specifically to their long-term interests as well as evolving employment landscape. The impact of this personalization can be amplified by digital twin technology, digital mentoring and counseling bots, or hybrid models that include human intervention.
I envision governments getting involved in organizing their national human capital development activity by mobilizing educational institutions to adapt to this new paradigm, using advanced technology to link the relationship between talent supply and demand, to prioritize using data science and AI to deliver what quantities to a company-wide matchmaking service between talent aspirations and available resources, and injecting a whole new level of sophistication into the development of human capital policies.
I see the need for the field of human resource management to transform from a set of speed bumps that aim to keep a cooperative and productive workforce
to that of maximizing the value and potential of human capital without being possessive while keeping broader societal goals in mind.
And I envision a world of individuals with equal access and resources who are free to rush into opportunities that suit them and ways to engage in cause-related behaviors that align with their values. and their ideals.