140 million full time jobs created or destroyed by knowledge work automation in the coming age of the machine: PART IV of our McKinsey study review

A looming wave of  knowledge work automation will generate or displace the equivalent of 140 million full times jobs by 2025 as it crashes and breaks upon the managerial class with same impact already felt by workers in the manufacturing and transactional sectors over the last half a century.

Machines will learn, adjust and reprogram themselves and the vast and ever growing data sets underpinning that machine learning will make the robots better decision makers than the humans who deploy them.

The jobs won’t all necessarily be lost, as technology will also make many workers more productive, but as always there will be losers, according to McKinsey and Company in their report into the most disruptive technologies for the next decade.

In the applications we sized we estimate knowledge work automation  tools and systems could take over tasks that would be equal to the output  of 100 million to 140 million FTEs. This could have an economic impact  of between  $5.2 and $6.7 trillion by 2025.”

The biggest impacts will be felt in the developed world by virtue of the cost of labor for the managerial and executive class in those markets, however for the developing world it is a two edged sword.

One the one hand knowledge work automation will be a great leveler allowing emerging economies to be more competitive. However growth from trends such as off-shoring is likely to be tempered as companies find technology at home cheaper than labor overseas.

Professionals in the administrative and clerical sectors and social services,  along with the technical professionals and management will most upended.

According to the authors, “As we have seen in previous waves of manufacturing and transaction work automation these changes can happen faster than social institutions can adjust. And while previous productivity gains have generally  resulted in the emergence of new high-value- added jobs, it is not always the displaced workers who benefits most from these opportunities.”

McKinsey and Co. defines knowledge work as “The use of computers to perform tasks that rely upon complex analysis, subtle judgments and creative problem solving.”

The authors say it is made possible by advances in three areas, ongoing computing technology improvements (basically Moores Law) , machine learning and natural user interfaces

These capabilities extend computing into new realms such as being able to learn and make basic judgments  but they also create new relationships between knowledge workers and machine, say McKinsey. “It is increasingly possible to interact with a machine the way one worked with a co-worker.”

“Instead of asking a co-worker to pull all the information on the performance of a certain product in a specific market or waiting for such a request to be turned into a job for the IT department, a manager or exec could simply ask a computer to provide the information.”

McKinsey says machine learning techniques give computers the ability to draw conclusions from patterns they discern is massive data sets. Importantly computing learning no longer relies on fixed algorithms written by programmers.

Instead they can adjust and modify their own algorithms based on an analysis of the data , enabling them to see the relationships and links that a human might overlook.  Moreover these machines can learn and get smarter as they go along; the more they process big data, the more refined their algorithms become.”

Advances in technology, say McKinsey, will give computers the ability to respond directly to human commands and requests – its already happening with speech recognition and gestures.

The report notes that computers can  now act on unstructured command, answering a question posed in plain language – and even make subtle judgments. “They can sift through massive amounts of information to discern patterns and relationships. They can “learn” rules and concepts based on examples or simply by crunching data. And with advanced interfaces and  AI software they can understand and interpret  human speech, actions and even intentions from ambiguous commands.”

The implications for today’s knowledge workers, particularly in the advanced economies are huge and not all positive.

“Such tools could both extend the powers of human workers and allow them to offload tedious detail work. But these tools could also lead to some jobs being automated entirely.”

In keeping with the tone of the rest of its study, McKinsey and Company tends to say focused on the positive.

Two examples in particular stand out.

Education:  ”A company called Measurement Incorporated won a $100,000 prize from the Hewlett foundation in 2012 for developing technology that enables a computer to grade student written responses including essays as well as a skilled human grader can do,

Healthcare: “Oncologists at memorial Sloan Kettering Cancer Centre in new York are using IBM’s Watson supercomputers to provide chronic care and cancer treatment diagnostics by accessing knowledge from 600,000 medical evidence reports, two million pages of text from 42 medical journals and 1.5 million patient records from clinical trials from oncology. It can then compares each patient’s individual symptoms, vital signs, family history , medications and genetic makeup, diet and exercise routine to diagnose and recommend a treatment plan with the highest probability of success.”

Whether we are entering a robotic dystopian nightmare or a capitalist’s utopia – or both – will still depend on overcoming some significant impediments.

Artificial intelligence for instance is a technology with a long heritage of shrinking to the occasion. The authors say, “While showing remarkable  advances it will still have to develop significantly before the scale of benefits  we estimate here can be realized.”

And of course the kinds of upheavals presaged in the report suggest massive organizational and cultural challenges leading many companies to delay adoption of knowledge work automation until the technology is clearly proven.

Companies  will also need to make careful choices around priorities. The culture of cutting from the bottom which has underpinned outsourcing and off-shoring initiatives for two decades may be flipped on it head if the authors are correct. For instance they say, “The biggest benefits may come from applying knowledge work automation to boost the productivity of employees in high value add functions, rather than focusing on simple tasks that might be turned over to machines.”

Of course there is a slight problem .  To exploit the benefits of the automation of  knowledge work much of the organizations intelligence will need to first be codified often by the very workers who are being  replaced by this technology.

 ”This could create challenges for employers looking to obtain robust employee support for adoption and will require careful communication and change management.” You reckon?

The automation of knowledge work has the potential to become pervasive, transforming  the economics of many industries but also posing challenges and opportunities for tech providers, virtually all business leaders, individuals band policy makers, ” the report concludes

 And a postscript. You will be glad to know the IT industry wins again.

“Many companies will need support in change management, technical installation, process redesign, and employee training as they upgrade their technology platforms. Technology providers, IT consultants and systems integrators are likely to find new opportunities to help business make these transitions  successfully, perhaps using knowledge work automation technology themselves to better manage projects and conduct advanced analysts.”

Once again the IT industry will blow up your business and charge you through the nose for the privilege. Technology is  a hell of a business.

Previous post

"The first thing we’ll do is kill all the bankers." Google, P2P lending, and the next World War Web

Next post

Tumblr surges since Yahoo deal, averaging 250,000 new blogs and 80,000,000 new posts a day.