Tag: AI

Steve Jobs’ “bicycle for our minds” and the current standoff between office centralists and virtualists

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The microcomputer is the “bicycle for our minds” as it was termed  by Apple co-founder Steve Jobs. The Internet the multi lane bike path over which we cruise along, steering with our keyboards, mice and monitors.

The world of knowledge work didn’t adjust well to Steve Jobs’ bicycle. The reason is it began the obsolescence of commuting Arthur C. Clarke predicted in his 1964 City of the Future video. A lot of orgs however chose to shun the bicycle and have staff trek to a centralized, commute in office (CCO) just as they did for decades before personal computing and later, personal communication devices.

They basically told their staffs, “You can ride a bicycle and should learn to do so. But only with company issued bicycles that must be ridden only on company premises.” That policy derives from the mainframe and minicomputers that preceded PCs that were located at company offices. And later, file servers. All kept in “computer rooms” in offices before they were chained together in server farms to power the cloud. The computer is in the office and therefore so must be the users.

That paradigm continues to play out today with the continuing expectation of knowledge organizations that the CCO is the only place where real knowledge work can be done. Hence, the tensions between the virtualists who see their home office as just suitable and the centralists, managers who expect staff to be in the office on designed days or number of days each work week. And return to the CCO starting in 2022 as the COVID-19 pandemic waned and social distancing protective measures ended.

These are very different views of the world of knowledge work roiled by rapid advances in information and communications technology. The latest being generative artificial intelligence that could make Steve Jobs’ microcomputer bicycle like a modern one with electronic gear shifting. Or into a fast motorbike that can even drive itself.

These advances will fuel a new debate, this one on AI’s role in knowledge work and how knowledge workers should best use it.

From Office to Output: Redefining Knowledge Work

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In the first half of the 2020s, two developments emerged with major implications for knowledge work.

The first is virtualization that is deemphasizing when and where it’s performed. The social distancing public health measures of the COVID-19 pandemic saw a tipping point for the longer term trend of information and communications technology (ICT) advances connecting knowledge workers outside of co-located office settings, effectively obsoleting the daily commute.

Then in 2022-23, another ICT development emerged: generative artificial intelligence accepting plain language queries and largely replacing traditional web searches, synthesizing and greatly speeding up access to online information. On its heels came agentic AI that can analyze data, set goals, and take independent actions at the direction of knowledge workers.

Both developments have the potential to profoundly alter knowledge work as we know it, which has been traditionally defined by doing defined tasks while present in a centralized, commute-in office during scheduled work hours.

One likely outcome is knowledge work will be more defined by outputs and deliverables rather than inputs and presence in an office. That could mean dispersed, small project teams that form up for the purpose of completing a project and disbanding when it’s accepted by the sponsor as complete. They may meet up in a co-located setting. Or not, depending on project needs and the team’s preference.

For the knowledge workforce, the implications are similarly sizeable. Less permanent employment by a single knowledge organization. More projectized contract work arrangements where specific subject matter expertise and experience is required. These contractors may work independently or as part of a professional services firm.

This points to a decline in employment in the conventional sense where knowledge work is defined by the terms and conditions of the employer: when, where and how work is to be done.

That in turn has implications for medical care finance in the United States where employers are mandated by state laws to pay for medical care arising from job duties and for large employers, medical benefit plans for non work-related care.

The knowledge work diaspora

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Knowledge work — also referred to as thought work — aims to develop information into actionable plans and reach decisions about them. For private sector organizations, that includes product or service development, marketing strategy and planning logistics and access to resources. For governments, it’s how to implement public policy and develop programs and budgets to support them.

None of these functions necessarily require knowledge workers to gather regularly in dedicated office space though they might find it beneficial to gather on occasion, perhaps in a day or week-long intensive Kanban or brainstorming session as well as to strengthen social bonding among team members. With communication and collaboration possible from most anywhere to perform these functions, a physical space now must demonstrate that benefit since the traditional office it is no longer the default setting for knowledge work. Nor is it practical or cost effective for large numbers of knowledge workers to regularly commute to one.

This fundamental shift in knowledge work has produced a knowledge work diaspora out centralized commuter offices. It’s upending our concept of knowledge work. Some knowledge organizations that have traditionally viewed their workforces like factory parts inventories are physically inventorying them in office spaces. They have done so by ordering their staff members to report to offices – referred to as “return to office” for what is effectively a census of commitment. If they are not there, they’re not counted, discounted for promotions and even dismissed. They are reassessing the size of their staffs and future office space needs since both of these have been traditionally measured by staff office presence.

The rapid emergence of AI in knowledge work adds a new wrinkle. It requires sizable space for its servers, but unlike humans doesn’t need office space. It too will hasten the diaspora of knowledge work as it was known before ICT began to change it decades ago.

This is a time of great change among knowledge workers and organizations that will require rethinking and adjustment. Or what futurist Alvin Toffler described as developing a form of postmodern literacy when he said “The illiterate of the future are not those who can’t read or write but those who cannot learn, unlearn, and relearn.”