Feb 192017
 

 

The statistics continue to come about the challenging future of work with the Harvard Business Review looking at how artificial intelligence is changing the role of knowledge workers and the World Economic Forum reports how Japan is already well down the track of automating many ‘white collar’ roles.

A couple of decades or so back, the assumption was ‘knowledge work’ represented the future of employment and the thought of management being replaced by computers or robots was unthinkable.

That hasn’t proved to be so as the low end jobs, which we thought would be taken up by displaced industrial workers were offshored, subject to a ‘race to the bottom’ in pay rates and, now, are increasingly becoming automated.

While the robots first came for call centre workers, it’s quite likely the next wave of will affect white colour workers reports Dan Tynan in The Guardian who has an overview of some of the likely fates of various occupations.

A good example of the shift, are lawyers with Tynan citing the company DoNotPay which uses AI to help customers fight traffic infringements as an example of the legal profession being automated out.

Bad for young lawyers

This though isn’t new in the legal profession. Over the past twenty years many roles in fields such as property conveyancing and contract drafting have been offshored, so much so that junior lawyer’s payrates and job prospects have collapsed as entry level jobs have dried up.

How the legal profession has used automation and offshoring is a good indicator of how these tradition industries are evolving, now a senior lawyer can handle more work and the need for juniors and paralegals is reduced. The work stays with the older worker while younger workers need to look elsewhere.

While Tynan discounts the effects of automation on the construction and health industries, those sectors are similarly being changed. Robot bricklayers, for example, allow older workers to stay in the industry longer and increase productivity.

The internet of things and artificial intelligence are similarly taking the load of nurses and doctors while making diagnostics faster and easier with major ramifications of these industries.

Dirty data

There are weaknesses in a data driven world and this gives us clues to where the future jobs may lie, the Harvard Business Review optimistically notes many roles can “composed of work that can be codified into standard steps and of decisions based on cleanly formatted data,” however obtaining ‘cleanly formatted data’ is a challenge for many organisations and managing exceptions, or ‘dirty data’ feeds, shouldn’t be underestimated.

Unexpected consequences exist as well, the media industry being a good example. While the demand for content has exploded, the rise of user generated content on social media and the collapse of advertising models has upended publishing, writing and journalism. While artificial intelligence and animation can replace actors and reporters, it hasn’t done so in a major way yet.

How industry sectors will be affected by automation is something the US Bureau of Labor Statistics looked at in 2010.

The roles which the US BLS estimates may be less affected by automation may be more affected than we think – how the retail and media industries changed in the twentieth century is instructive where the models at the beginning of the century were upended but by the end of the millennium employment in those sectors was higher than ever.

The future of work isn’t obvious and the effects of automation bring a range of unforeseen consequence and opportunities – this is why we can’t rest on our laurels and assume our jobs, trades and professions will be untouched by change.

Feb 082017
 

“Neo liberalism is dead” was Paul Mason’s opening for his talk ‘Will Robots Kill Capitalism?’ At Sydney university on Monday night.

Mason, who was promoting his book ‘Postcapitalism: A Guide to Our Future’ was exploring how we create an alternative to the failing neo-liberal world while avoiding the failings of the past.

Describing the current ennui towards establishment politics as being “the biggest change since the fall of the wall in 1989,” Mason believes that the neo-Liberal, pro-markets, view of the world is now failing because the general population increasingly can’t afford the credit which powers the current system.

Increasing voter hostility

With increased insecurity the general population’s hostility towards the global elites is only going to increase, Mason says, as a low work future is traps people into low income ‘bullshit jobs’.

Mason describes a bullshit job as being something like the hand car washes that have popped up around UK (and Australia) where workers are paid the absolute minimum to provide a service cheaper than any machine.

With bullshit jobs, it’s hard not to consider the white collar equivalent – just yesterday The Guardian, which Mason writes for – described a report by UK think tank Reform which suggested 90% of British public service jobs could be replaced by chatbots and artificial intelligence.

It’s easy to see those same technologies being employed in the private sector as well with middle management and occupations like Human Resources and internal communications being easily automated out by much flatter organisations.

A low work future

The result of that, which we’re already seeing, is increasingly profitable corporations that barely employ anyone.

However for companies like Google, Facebook and Apple those business models also present risks as they are valued by the market far beyond any reasonable expectation of return – even if they do manage to eat each other.

Another risk to today’s tech behemoths is the commoditization of many of their industries. “Not all of the high tech economy will be a high value economy.” Mason point out, going on to observe that Google may have recognised this in carrying out their Alphabet restructure.

The neoliberal Anglos

Not all countries though have followed the Anglo Saxon neo-liberal model over the past forty years though. In what Mason describes as “The yin and yang of globalIzation,” he point out China, Germany, Japan and South Korea Have focused on production and raising living standards while the English speaking nations enforced austerity on their populations with large groups being left behind both socially and economically.

Which leads to Mason’s key question, “will the low work future see neoliberalism replaced by ‘neo-feudalism’ or something more enlightened?”

To support the latter, Mason suggests a transition path into the ‘low work future with the following features;

  • automation
  • basic income
  • state provided cheap, basic goods
  • externalising the public good
  • attacking rent seeking
  • promoting the circular economy
  • investing in renewable energy

That list seems problematic, and at best hopelessly idealistic, in today’s economies – particularly in the neoliberal Anglosphere.

A need for new mechanisms

Mason’s points though are important to consider if we are facing a ‘low work’ society as there has to be some mechanisms to allow citizens a decent standard of living even if the bulk of the population is unemployed.

Even if we aren’t facing a low work future, the transition effects we’re currently experiencing where many of today’s jobs are going to be automated away threaten serious political and economic dislocation in the short to medium term.

What Mason reminds us is that the political and economic status quos can’t be maintained in the face of dramatic technological change. We have to consider how we’re going to manage today’s transformations so we don’t end up in a neo-feudal society with the discontent that will entail.

 

Dec 212016
 

What happens when the founder and CEO of one of the world’s biggest tech companies decides to create a genuinely smart home? Facebook’s Mark Zuckerberg spend 2016 finding out.

“My goal was to learn about the state of artificial intelligence — where we’re further along than people realize and where we’re still a long ways off,” Zuckerberg writes in a blog post.

The immediate problem Zuckerberg faced in creating his home made Jarvis automation system was many household appliances are not network ready and for those that are,  the proliferation of standards makes tying them together difficult.

For assistants like Jarvis to be able to control everything in homes for more people, we need more devices to be connected and the industry needs to develop common APIs and standards for the devices to talk to each other.

Having jerry rigged a number of workarounds, including a cannon to fire his favourite t-shirts from the wardrobe and retrofitting a 1950s toaster to make his breakfast, Zuckerberg then faced another problem – the user interface.

While voice is presumed to be the main way people will control the smart homes of the future, it turns out that text is a much less obtrusive way to communicate with the system.

One thing that surprised me about my communication with Jarvis is that when I have the choice of either speaking or texting, I text much more than I would have expected. This is for a number of reasons, but mostly it feels less disturbing to people around me. If I’m doing something that relates to them, like playing music for all of us, then speaking feels fine, but most of the time text feels more appropriate. Similarly, when Jarvis communicates with me, I’d much rather receive that over text message than voice. That’s because voice can be disruptive and text gives you more control of when you want to look at it.

Given the lead companies like Amazon, Microsoft, Google and Apple have over Facebook in voice recognition, it’s easy to dismiss Zuckerberg’s emphasis on text, but his view does feel correct. Having a HAL type voice booming through house isn’t optimal when you have a sleeping partner, children or house guests.

Zuckerberg’s view also overlooks other control methods, Microsoft and Apple have been doing much in the realm of touch interfaces while wearables offer a range of possibilities for people to communicate with systems.

The bigger problem Zuckerberg identifies is with Artificial Intelligence itself. At this stage of its development AI struggles to understand context and machine learning is far from mature.

Another interesting limitation of speech recognition systems — and machine learning systems more generally — is that they are more optimized for specific problems than most people realize. For example, understanding a person talking to a computer is subtly different problem from understanding a person talking to another person.

Ultimately Zuckerberg concludes that we have a long way to go with Artificial Intelligence and while there’s many things we’re going to be able to do in the near term, the real challenge lies in understanding the learning process itself, not to mention the concept of intelligence.

In a way, AI is both closer and farther off than we imagine. AI is closer to being able to do more powerful things than most people expect — driving cars, curing diseases, discovering planets, understanding media. Those will each have a great impact on the world, but we’re still figuring out what real intelligence is.

Perhaps we’re looking at the what intelligence and learning from a human perspective. Maybe we to approach artificial intelligence and machine learning from the computer’s perspective – what does intelligence look like to a machine?

Nov 232016
 

Should we be rethinking how computers are designed? The co-founder and CEO of chip designer Nervana, Naveen Rao, believes so as artificial intelligence applications change the way systems work.

“A brain only uses 20 watts of power to do far more than a laptop,” observes Naveen Rao at a breakfast following Intel’s Artificial Intelligence Day in San Francisco last week.

“Presumably the brain is doing more computation than your laptop,” he continues. “What are we missing? Why is there such a big difference between what a computer can do and a brain can do. Let’s try to understand that and maybe what we learn can change how we design computers.”

A lifetime passion

Rao, whose company was acquired by Intel for over four hundred million dollars last August, was discussing the quest to make computers operate more like brains and less like adding machines.

For Rao this has been a lifetime passion, having graduated as an electrical engineer and spending most of his career designing computer chips at Sun Microsystems and various startups he quit his job to do a PhD in neuroscience, “after ten years, I wanted to return to my passion of trying to use biology to better understand computers.”

From that combination of study and experience Nervana was founded in 2014 and raised twenty million dollars from investors before being acquired by Intel.

Replicating the bird, not the feathers

The key part in creating a computer that acts more like a brain is to get the individual CPUs to be working together in a network similar to the mind’s neural paths, “look at a bird compared to a plane.” Rao says,” we don’t replicate the feathers, but we do the function.”

Doing this meant rethinking how processors are designed, “there are tried are true methods of chip architecture that we basically questioned.”

“We don’t need high levels of generality. We don’t need this to work on energy or weather simulations. We removed some of that baggage.”

Paring back the processor

So the Nervana team stripped down the individual processor and removed many functions, such as a cache, that are built into today’s advanced CPUs. Those lighter weight, and less power hungry, units can then be combined into neural networks more suited to artificial intelligence functions than today’s computers.

“Nvidea, this sort of fell into their laps,” observes Rao of Intel’s key competitor in the AI, graphics and gaming space. “It just so happens the graphics functions on their chips are suited to Artificial Intelligence applications.”

Without the more complex functions of modern CPUs, Rao and the Nervana team see the opportunity to build more flexible computers better suited to artificial intelligence applications.

Intel focuses on AI

That focus on AI has seen Intel branding its AI initiatives under the Nervana brand name as the iconic Silicon Valley company tries to move ahead with more nimble competitors like Qualcomm and NVidea.

For the computer industry, artificial intelligence promises to be the next major advance, something necessary if we are ever going to make sense of the masses of data being collected by smart devices and the reason why Microsoft, Google, Amazon and Facebook are all making massive investments in the field.

Regardless of whether Intel and Nervana are successful in the AI marketplace, Rao sees the entire field of neural computing as a great opportunity. “It’s exciting, there’s lots of chances to innovate.”

Paul travelled to San Francisco as a guest of Intel

 

Jul 302016
 
Nokia Lumia 920 has an impressive camera

Last week Microsoft quietly buried its smartphone ambitions with the announcement they would shed 1,850 jobs largely from the remains of the Nokia business they acquired four years ago.

Microsoft’s Lumia exercise was expensive for the company but even more costly in terms of missed opportunities.

Those opportunities are now in cloud computing and artificial intelligence services. Shareholders will be hoping the current CEO Satya Nadell executes a lot better on them than his predecessor did with smartphones.

Jul 282016
 

Currently Microsoft are running their Imagine Cup, the company’s annual student developer competition at their Seattle head office.

A regular fixture for the last 14 years, the Imagine Cup is Microsoft’s opportunity to show how emerging applications can be based upon their technologies. It tells us as much about the company’s successes as it’s missed opportunities.

With Artificial Intelligence and machine learning being the upcoming battlegrounds for the software giants, it’s not surprising many of this year’s competitors are focused on applying those technologies.

A good example of this is the Ani platform of Australia’s entrant, Black.ai, which analyses spatial movement and biometric information. In many ways this adds intelligence to smarthomes and has immediate applications in fields like aged patient care.

Black.ai’s timing is very good as patient monitoring has become an issue in their home country and veteran tech investor Mark Suster predicts tracking the flow of people is going to be a huge market.

The patient care angle of Black.ai’s  is particularly pertinent to the Imagine Cup competition as health services have been a focus in the past. Two years ago the winners were another Australian medical services platform, Eyenaemia that used a smartphone app to detect anemia.

While the Imagine Cup is a good showcase for Microsoft, the competition also shows how the market has evolved around the company. Most of the contests have a smartphone component and the cloud features heavily in all the applications, both are fields where Microsoft has either struggled or is playing catch up.

The focus on cognitive computing and artificial intelligence in this year’s event shows the company is keen to show off its prowess in the emerging battle with Amazon, Google, Apple and no doubt other companies. Microsoft will be hoping they won’t be left behind in the next wave of computing.

Apr 012016
 

Despite the embarrassment of their foul mouthed racist bot, Microsoft are pressing on with a move into artificial intelligence.

Ahead of this week’s Launch event in San Francisco, Microsoft’s CEO Satya Nadella laid out his vision for the company’s Artificial Intelligence efforts in describing a range of ‘bots’ that carry out small tasks.

Bloomberg tagged Nadella’s vision as ‘the spawn of clippy’, referring to the incredibly irritating help assistant Microsoft included with Office 97.

Tech site The Register parodied Clippy mercilessly in their short lived IT comedy program Salmon Days, as shown in this not safe for work trailer. While The Reg staff were brutal in their language and treatment of Clippy, most Microsoft Office users at the time shared their feelings.

While Clippy may be making a comeback at Microsoft, albeit in a less irritating form, other companies are moving ahead with AI in the workplace.

Robot manufacturer Fanuc showed off their self learning machine a few weeks ago which shows just how deeply AI is embedding itself in industry. Already there are many AI apps in software like Facebook’s algorithm and Google’s search functions with the search engine’s engineers acknowledging they aren’t quite sure what the robots are up to.

For organisations dealing with massive amounts of data, artificial intelligence based programs are going to be essential in dealing with unexpected or fast moving events. Those programs will also affect a lot of occupations we currently think are immune from workplace automation.