The Future of Questions

Computers are useless; they can only give you answers”. Pablo Picasso

For anyone paying attention – as I know, dear reader, you are – you’ll have no doubt noticed that the debate about artificial intelligence is becoming almost as intense – almost – as the US Presidential campaign.

Every day new articles, new movies, new TV shows, new conferences, new books, appear, warning us that the robots are coming. The latest recent gathering of the global socio-economic elite, in Davos – Woodstock en Piste – majored on the role of AI in the “4th Industrial Revolution” and the impact AI will have on the future of jobs. If there was a Sypder Index Fund tracking AI commentary (traded algorithmically, naturally – pun intended) it would be worth stuffing into your 401k.

There are, of course, many similarities between the AI debate and the political one; both are really, as the WEF recognized, about the future of work; how to get work, how to secure work, what work fundamentally is, in an age where code can do more and more things that humans have traditionally traded for money. And both are examining the nature of artificially; “authenticity” versus “political expediency” is a central tenant of the political race; “wetware” versus “software” is core in the race against the machine.

And just as in the political debate, the loudest, most extreme voices seem, at present, to be capturing most of the oxygen in the room. For Trump and Sanders in politics, read Kurzweil and Musk in AI. For Ray Kurzweil the singularity is near. For Elon Musk, AI represents “our greatest existential threat”.

As per usual your humble correspondent can see both sides of the argument. (In my defense your honor, I present F.Scott Fitzgerald’s famous words, “The test of a first-rate intelligence is the ability to hold two opposing ideas in mind at the same time and still retain the ability to function”). On the one hand it’s not hard to imagine that the offspring of the computer that won Go http://bit.ly/1PTnLAK aren’t going to stop there. On the other hand though, a future where people are oppressed by malign machines seems straight from a back lot in Hollywood or Watford; fun to chew on with some popcorn on a Saturday night but hardly something your angst needs to grind on right now.

If you are increasingly anxious about the rise of machine intelligence though I’d strongly recommend the recent book What to Think About Machines That Think http://amzn.to/1QEAPg6 edited by John Brockman, Editor and Publisher of the very cool http://edge.org/ Brockman has rounded up essays by a lot of top wetware including Paul Saffo, Tim O’Reilly, Kevin Kelly, Nick Bostrom, and Esther Dyson, amongst many others, who all take different cracks at figuring out quite how worried/excited/blasé we should be. If there’s a consensus amongst the thinkers about what to think about machines that think it’s pretty hard to discern. Better software than what I have on board would be needed to figure that out. There are some, like Bruce Schneier from Harvard Law School, who wonder what happens when a omputer (not its operator) breaks the law. Others, like Josh Bongard from the University of Vermont, suggest that when “machines are commanded to “survive, reproduce, and improve in the best way possible” they will probably give us humans a very short window to relish that insight”. But then again, others feel aligned with Steven Pinker from the Department of Psychology at Harvard, who writes “My own view is that the current fears of computers running amok are a waste of emotional energy – that the scenario (i.e. the rise of AI) is closer to the Y2K bug than the Manhattan Project”.

Which brings me full circle back to that primo piece of wetware (not featured in Brockman’s book) Pablo Picasso. In 1968, when he made the remark above, computing was – as seen from 2016 – in its infancy. But it was powerful enough to fire the imagination of many who wondered where software would take us and what it would be like when we got there. Arthur C. Clarke was worrying about HAL. Philip K. Dick was dreaming of electric sheep. Michael Moorcock was already leaping ahead to speculate about the final program (US spelling!). It wasn’t hard, even then, to extrapolate that software would get cleverer and cleverer and one day get cleverer than us. Of course the Turing Test was already almost 20 years old by then, long enough for the kings of the swingers to worry how long they’d be the jungle VIPs (Disney’s The Jungle Book came out in 1967 ...)

Picasso though was less impressed and less concerned. His, at first gnomic, but on reflection, devastatingly profound statement, was spot on then, but even more spot on – even with the technological advances of the last 50 years – today. Computers have gotten great at giving us answers; ask Siri “what does the fox say” and she’ll (!) correctly answer “fraka-kaka-kaka-kaka-kow”. Waze will tell us to avoid Route 17 because there’s just been a fender bender. Zapier will automatically create a Google Calendar event from an Evernote reminder. IFTTT will tell your family when you’re on the way home from work. But these are still all answers. We – the wetware – are still thinking of the questions. Even on the very far edge of the new frontier – the aforementioned game of GO – the real VIPs are humble and understated in their claims for where things stand; “It’s (sci-fi AI) very, very far in the future from the kinds of things we’re currently dealing with, which is playing Pong on Atari”, Demis Hassabis told the FT last year http://on.ft.com/1P3i59q. This nice compilation of quotes http://read.bi/1GTtZge, rounded up by Business Insider, also injects a dose of healthy skepticism from those really in the know.

Now I wouldn’t go quite as far as Old Pablo in saying computers are useless; I quite like my iMac, iPad, PC, Apple Watch, E20, TV, car, etc etc (computers one and all). But I do think that Pablo Diego José Francisco de Paula Juan Nepomuceno María de los Remedios Cipriano de la Santísima Trinidad Martyr Patricio Clito Ruíz y Picasso (would a computer think of that?) was onto something then and is still onto something now. We – not software – are the future of questions and questions remain more important than answers. Questions come first. Every answer begets a question.

Questions – curiosity –are/is (I would argue) the central defining characteristic of intelligence (as it is manifested in our human form). From our first words http://bit.ly/20ErHNk to our first steps to our first journey it is intrinsic to our very being to want to know who what why or where. Nobody tells us to ask questions. No parent, or teacher, or TV show, or social media feed tells us – programs us – to want to know “zup?” We just do. I wonder why? C’est une bonne question...

When computers start asking questions – “just what do you think you’re doing Dave?” – then I guess we can start worrying. But that – it seems to me – is as far as away in the future as it was 50 years ago.

I hope.

Please note that this is article was written by me, Ben Pring, not by Automated Insights or Narrative Science.


It's Tuesday Morning: How Can you Sustain Momentum for Intelligent Process Automation?

It’s not a radical fantasy to view software robots that automate business processes as disruptors of the “old way of doing things.” Intelligent automation is here, today. And there are some tangible steps that you can take to get started – quickly.

The Center for the Future of Work published our take in the whitepaper “The Robot and I” on a new and important type of robotics emerging that we call intelligent process automation (IPA). With IPA, smart machines augment and extend people’s uniquely human capabilities – empathy, creativity, problem-solving and drive – to deliver superior business results, using increasing levels of built on AI and machine learning. To really get going, there are steps you can start to take on Monday Morning that will get you on the journey to the future of processes.

Taking small steps can and should be done help break inertia. For example, if you’re not doing robotics because AI seems so overwhelming you’re not alone. But applying robotic automation tools is one easy step you can take on an intelligent process automation journey to machine learning and AI to run algorithms to analyze real-time customer credit worthiness in banks that can drive millions in savings, or – more importantly, in an industry like Health Care – things like spotting tumors in medical scans that could save people’s lives.

You may think you’re already on the path. New models like IPA – as opposed to true digital change – do provide an on-ramp to new efficiency and quality thresholds to rote work. But the emphasis on sheer people power is different and changing fast.

How will you respond? Scan your process topography and target processes (or fragments or pieces of sub processes, say, auto-adjudication in claims management) that might lend themselves to being low-hanging fruit for automation. Consider the following as a simple, yet effective checklist to begin the assessment:

  • Perform an automation readiness assessment. Map processes to a level of detail that includes inputs, processes and outputs. Scan the market for tested and ready-to-implement technologies that have established tangible proof of success. Apply minimally invasive automation technologies for efficiency gain today, but keep your eyes on the prize for where transformation for differentiation makes the most sense tomorrow.

  • Analyze your company at the process level. Review in detail your processes as they exist today (new product/service development, sales and customer relationship management, operations, etc.). Infuse a digital process plan by re-imagining moments of customer engagement or constituent journeys. Target tangible process metrics: cost-per-claim, clinical trial yield, healthcare unit cost, fraud prevention rates, etc.

  • Help humans evolve toward the work of tomorrow. Start by giving employees access to digital processes and machines that help them do their jobs better, smarter and with more meaningful impact to the business. It’s not about the number of people tied to “doing the process;” it’s about outcomes and making smart people even smarter.
  • Create, educate and inculcate “the vision.” Move from recognizing that something “needs to happen” to “making something happen.” Business processes — automated, digital or otherwise — are useless if they don’t support a business strategy. That means helping smart people make smarter decisions in support of differentiating activities. Get true alignment and buy-in to design, develop and deliver — and move fast to get “runs on the board” to maintain and sustain interest.

  • Assign “tiger/SWAT teams,” including a mini-CIO (plus experience/design).Most IT professionals are hard pressed to fulfill the demands of current delivery, but there are likely many extremely valuable (and digitally-savvy) resources that would jump at the chance to become automation experts or join a digital processtiger team. Physically sit and co-locate these digital process change agents into the BUs.
    • Keep them thinking about the new process anatomy, data and the “art of the possible,” including participatory design/research principles.
    • Have them re-code moments of engagement (internal and customer-facing), using new technologies of intelligent automation.
  • Execute specific process projects — to learn fast, or “fail fast.” Be specific — don’t place resources and “hope for the best.” IT resources landing in a business unit without work assignments are often quickly marginalized and abandoned. Get creative and get moving — but within the “swim lanes” of the business or process strategy. Identify, develop and implement solutions for process automation or digital business transformation — fast — to successfully outrun the competition.

  • Make “meaning-making” mean something powerful — fueled by process data. The imperatives to “do analytics” or “use big data” are just too broad to be meaningful. Instead, focus on a specific business process. Whether it’s your underwriting process, clinical drug trials, wealth management service, supply chain or customer relationship management process, focus on work that shapes at least 10% of your costs or revenues. To seize competitive advantage, look at the data that is — and could be — exchanged and used for value.

IPA is here today – it’s quickly accelerating and disrupting the status quo. It sets a scene for smart automation built and operated by smart people freed from the humdrum who focus on creating greater business value. Understanding the symbiotic relationship between humans and robots is crucial to understanding what the future holds. After all, the human spark is, and will remain, essential to how knowledge work is orchestrated and managed. What’s different is that technologies can now create more effective knowledge workers while simultaneously generating and capturing data that can improve and even transform processes, along with eliminating wasteful steps.

Our research opens the aperture on the possibilities. Some of them are intriguing, some are mind-bending, but all will usher in profound change. This is one of the most important trends in business services, and organizations need these insights to help them win in the era of automation and digital processes. And like a good science fiction movie, whether you like it or not, it’s coming soon — to a process near you.

To learn more, our research in “The Robot and I” reveals new market insights that chart the progress in the journey so far, where process change is most likely to occur next in specific industries and, importantly, what you should do about it.

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Ambiguity and Digital Transformation

     “Success in the future is found in ambiguity and chaos, not in the obvious and stable.” ~Kevin Benedict

We will never have complete and perfect information, or a full understanding.  We are bound to operate in an environment of ambiguity, meaning unclear, uncertain and difficult to comprehend. We have a decision to make.  We can use ambiguity as an excuse for inaction, or we can accept ambiguous environments as the norm and learn to thrive in them. 

Today we are facing unprecedented rates of change in consumer behaviors (watch Cutting Through Chaos in the Age of Mobile Me), which are increasing ambiguity levels and forcing enterprises to digitally transform.  This is happening at the same time as we are analyzing more data than ever before.  The challenge is less about increasing the volume of data, and more about finding the meaning in the data and associating it with relevant actions.

We humans seem to prefer solving problems, facing challenges and overcoming obstacles as a way to create stable and predictable environments.  We like to solve challenges and be done with them.  What happens, though, if we can’t be done?  What happens if our biggest challenge is change, and the increasing pace of change?  What happens in a world where as soon as a problem is solved, it needs updated and revised again because of perpetual change. 

Change is not to be solved; rather it needs to be embraced, navigated and exploited.  Change is the energy that propels companies forward into new innovations and opportunities.  Rarely will you find opportunities of significance where change is not found.

As the tempo of change increases and we move beyond “human time” into “computing time”, we must adopt new strategies for succeeding in ambiguity.  I propose that the economic winners of tomorrow will be companies that recognize knowing the unknown, is equally important as knowing the known.  They will implement strategies and define processes that let them operate in a fluid, agile environment, always collecting and analyzing new data and perpetually adjusting to new realities.  They will not as a goal seek stability, rather they will employ strategies for succeeding inside of constant change, chaos and ambiguity.  They will understand the biggest opportunities for success in the future will lie not outside, but inside of ambiguity.

"The future is coming fast and will not slow down for your budget priorities." ~Kevin Benedict