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If you need to do a job more than once then automate it - or so the wisdom goes. And now the growing availability of intelligent, automated software - or bots - is making automation a reality for businesses of all sizes.

Though US-centric, this Pew Report "Public Predictions for the Future of Workforce Automation" gives some insight to workforce attitudes to automation. Despite their expectations that technology will encroach on human employment in general, most workers think that their own jobs or professions will still exist in 50 years. Heads in the sand, or justifiable pessimism?

The Cabinet Office has selected Capgemini as its partner for a £4m project to try and drive use of robotic process automation (RPA) technology across Whitehall.

"Advice to the Prime Minister on opportunities in robotics, automation and artificial intelligence for the UK."

"Artificial intelligence and increasing automation is going to decimate middle class jobs, worsening inequality and risking significant political upheaval, Stephen Hawking has warned."

In 2015, Davenport and co-author Julia Kirby published "Beyond Automation" in the Harvard Business Review, in which they laid out five practical steps workers may take to improve their employability against machines.

"The automation of work by machines, including AI, and the increasing interconnectedness between people, machines, and ideas. In the book, Only Humans Need Apply, the authors identify five ways that people can adapt to automation and intelligent machines."

"Innovations in digitization, analytics, artificial intelligence, and automation are creating performance and productivity opportunities for business and the economy, even as they reshape employment and the future of work."

From science fiction to business fact. 45% of activities - not jobs can be automated. Quarter to a third of CEO's time can be automated.

What does the future of work look like

While automation will eliminate very few occupations entirely in the next decade, it will affect portions of almost all jobs to a greater or lesser degree, depending on the type of work they entail.

The TERMINUTER app is an automated cognitive meeting minutes tool, mainly based on speech-to-text technology. The app automatically writes and structures meeting minutes with decisions and to-dos and even alerts you if owners or deadlines are not defined.

As automation technologies such as machine learning and robotics play an increasingly great role in everyday life, their potential effect on the workplace has, unsurprisingly, become a major focus of research and public concern. The discussion tends toward a Manichean guessing game: which jobs will or won't be replaced by machines?

Despite improvements in cognitive technologies, that dream managerial scenario is still far from reality. Decisions that executives face don't necessarily fit into defined problems well suited for automation.

Google Search itself provides one of the most familiar examples of predictive intelligence. When you enter keywords in the search box, Google predicts what you are interested in and then presents you with results that match that intent. Since it released the first version of its Prediction API in 2010, Google has made some of these methods available to developers. Adoption among developers has not been high because machine learning requires a lot of infrastructure and validation to produce accurate results. Developers have also reported discomfort with basing products on black box APIs.

Humans are biased, and the biases we encode into machines are then scaled and automated. This is not inherently bad (or good), but it raises the question: how do we operate in a world increasingly consumed with "personal analytics" that can predict race, religion, gender, age, sexual orientation, health status and much more.

Workers looking for jobs in 2035 might consider retraining as remote-controlled vehicle operators or online chaperones. Those are two of the jobs of the future suggested in a report by the CSIRO that charts 20-year trends in increasingly digitally focused and automated Australian workplaces.

"Relying on counterfactual explanations as a means to help us act rather than merely to understand could help us gauge the scope and impact of automated decisions in our lives. They might also help bridge the gap between the interests of data subjects and data controllers, which might otherwise be a barrier to a legally binding right to explanation."

Installing thousands of bots has taken a lot longer and is more complex than most had hoped it would be. The 'robotics evolution' had stalled where companies try to scale the localised proofs of concept. #ai