Humans and Robot: Google I/O and Self Driving Bin Lorries

It’s Google’s big developer conference this week – I/O. So far centre stage has been given over to Artificial Intelligence and Machine Learning.

There are a set of articles that have been published, some of which I’ve highlighted below but I can summarise all of them with this one quote:

“We are now witnessing a new shift in computing: the move from a mobile-first to an AI-first world.”

Sandar Pichai, CEO, Google

For many the shift to mobile has made little impact on their day-to-day work, it’s had far more impact on their personal life. The switch to AI-first will have a massive impact across both our work and personal lives.

The keynote for I/O was just under 2 hours long, but thankfully The Verge have put together a 10 minute video of the highlights:

Also, Volvo have announced that they are working on a system for self driving refuse collection lorries. This is yet another self-driving initiative, but one with a specific purpose in mind. Instead of trying to resolve the generic problem of self-driving vehicles, in all contexts, this project is seeking to enable self-driving in the urban refuse collection context. Historically targeted innovations like this one are adopted prior to more generic innovations like self-driving cars:


Making AI work for everyone via Google

We are now witnessing a new shift in computing: the move from a mobile-first to an AI-first world. And as before, it is forcing us to reimagine our products for a world that allows a more natural, seamless way of interacting with technology. Think about Google Search: it was built on our ability to understand text in webpages. But now, thanks to advances in deep learning, we’re able to make images, photos and videos useful to people in a way they simply haven’t been before. Your camera can “see”; you can speak to your phone and get answers back—speech and vision are becoming as important to computing as the keyboard or multi-touch screens.


Partnering on machine learning in healthcare via Google

Our researchers at Google have shown over the past year how our machine learning can help clinicians detect breast cancer metastases in lymph nodes and screen for diabetic retinopathy. We’re working with Alphabet’s Verily arm and other biomedical partners to translate these research results into practical medical devices, such as a tool to help prevent blindness in patients with diabetes.

Now we’re ready to do more: machine learning is mature enough to start accurately predicting medical events—such as whether patients will be hospitalized, how long they will stay, and whether their health is deteriorating despite treatment for conditions such as urinary tract infections, pneumonia, or heart failure.


Why Google’s CEO Is Excited About Automating Artificial Intelligence via MIT Technology

Machine-learning experts are in short supply as companies in many industries rush to take advantage of recent strides in the power of artificial intelligence. Google’s CEO says one solution to the skills shortage is to have machine-learning software take over some of the work of creating machine-learning software.

Humans and Robots: What are you worried about? Machines in the home?

When it comes to risk the things that we rank highest in the machine learning world are physical things, in the UK at least. In a survey commissioned by the Royal Society it’s self driving cars and machines in the home that we give the highest risk to, we don’t think that health diagnosis technologies poses the same level of risk.

I find that intriguing, but not surprising, we are unnerved by the things that are physically close, but not the things that are hidden.

Whilst we are worrying about being physically harmed by self driving cars we don’t worry about predictive policing which could have a much greater impact on our society. This is a common problem, people aren’t very good at recognising the impact of things that are hidden because they are too blinded by the thing they can see. Like the conjurer’s misdirection we are too busy looking one way to see the thing that has just happened directly in-front of us.

Another interesting statement from the survey:

Results from the UK’s first in-depth assessment of public views on machine learning – carried out by the Royal Society and Ipsos MORI – demonstrate that while most people have not heard the term ‘machine learning’ (only 9% have), the vast majority have heard about or used at least one of its applications.

In other words, machine learning is having a significant impact on people’s lives even if they don’t recognise it.

This survey on social risk is published within a few days of an announcement by Durham Police (UK) that they are going to use artificial intelligence to help in the decision on whether, or not, a suspect should be kept in custody. How would you associate the social risk of such a system? I suspect that it depends on your background and how you regard the police.

It’s not really got anything to do with today’s theme, but I was quite intrigued to see that Google is setting it’s AI sights on musical instrumentation with a Neural Synthesizer, or NSynth. I’ve always been fascinated by the intersections of art and technology; pioneering artists have always embraced new technology to enable them to express their art. Music has been at the forefront of that pioneering so it will be interesting to see how musicians use these new technologies.


People are scared of artificial intelligence for all the wrong reasons via Quartz

People in Britain are more scared of the artificial intelligence embedded in household devices and self-driving cars than in systems used for predictive policing or diagnosing diseases. That’s according to a survey commissioned by the Royal Society, which is billed as the first in-depth look at how the public perceives the risks and benefits associated with machine learning, a key AI technique.


Durham Police AI to help with custody decisions via BBC

The system classifies suspects at a low, medium or high risk of offending and has been tested by the force.

It has been trained on five years’ of offending histories data.

One expert said the tool could be useful, but the risk that it could skew decisions should be carefully assessed.


Google’s creating sounds you’ve never heard before via Mashable

To create music, NSynth uses a dataset containing sounds from individual instruments and then blends them to create hybrid sounds. According to the company, NSynth gives “artists with intuitive control over timbre and dynamics and the ability to explore new sounds that would be difficult or impossible to produce with a hand-tuned synthesizer,” the company said in their announcement.

Humans and Robots: Augmented Productivity

For a few million years we’ve been augmenting our productivity with tools. Those tools helped us to catch more meat and to fight our enemies, in other words they made us productive. We continue to augment our productivity with new tools that help us achieve modern day productivity needs. Whilst productivity itself is a simple measure of input, added value and output it’s not always easy to define what the added value is. How people add value is going to be a key question as we transform the meaning of productivity in the coming years as the tools available change dramatically.

There have been a number of items highlighting these new tools over the last few days:

  • The MIT Technology Review is reporting on the impact of augmented reality on healthcare and the Operating Room in particular. The key thing here is that the information is augmenting the operating environment within the context of the operating environment.
  • Improbable has secured a $500m investment to help it continue to develop it’s simulation technologies. As Virtual Reality and Augmented Reality devices become more mainstream there’s the potential for a huge market in creating the simulations that bring those devices to life.
  • Cisco, Google and Microsoft have all made announcements aimed at augmenting today’s office productivity environment with various uses of AI.
  • And someone decided to make a robot that looks and moves like a spider (but only 6 legs so no needs to worry) 🙂

AR Is Making Its Way into the OR via MIT Technology Review

Doctors may soon be able to augment their view of your body, but it will be some time before it’s commonplace.

“Scalpel. Forceps. Suction. Oh, and nurse, pass me the HoloLens.”


If we’re living in a simulation, this UK startup probably built it via Wired

Improbable’s platform, SpatialOS, is designed to let anyone build massive agent-based simulations, running in the cloud: imagine Minecraft with thousands of players in the same space, or researchers creating simulated cities to model the behaviour of millions. Its ultimate goal: to create totally immersive, persistent virtual worlds, and in doing so, change how we make decisions.

Or more simply, as Narula often jokes, “Basically, we want to build the Matrix.”


How machine learning in G Suite makes people more productive via Google Enterprise Blog

According to a Google study in 2015, the average worker spends only about 5 percent of his or her time actually coming up with the next big idea. The rest of our time is caught in the quicksand of formatting, tracking, analysis or other mundane tasks. That’s where machine learning can help.


Transforming Collaboration Through Artificial Intelligence with Cisco’s Acquisition of MindMeld

Artificial Intelligence represents a tremendous opportunity to expand the reach and enhance the capabilities of enterprise technology. At Cisco, we have already been introducing AI into our solutions across security, orchestration, application performance and collaboration. Today, I’m excited to share Cisco’s intent to acquire MindMeld Inc., a San Francisco-based company that has developed a conversational platform based on natural language understanding (NLU). This acquisition, Cisco’s third in two weeks, represents how the buy pillar of our innovation strategy continues to impact our strategic shift to become more of a software company.


Microsoft’s Presentation Translator translates presentations in real time via TechCrunch

The Presentation Translator can automatically provide real-time translated subtitles or translate the text of their actual PowerPoint presentation while still preserving the original formatting.

In its current iteration, the service supports Arabic, Chinese, English, French, German, Italian, Japanese, Portuguese, Russian and Spanish. While the focus here is on translation, you also could use the same service to caption a presentation for audience members who are deaf or hard of hearing.


Man’s homemade robot spider looks real and we are sufficiently freaked out via Mashable

Humans and Robots: AI, AI, AI, AI

There have been several Artificial Intelligence (AI) articles over the last couple of days.

A number of these have been commentaries on some research put out by Gartner. The simplified story within the Gartner research is that things that professionals do today will be done by AI at a significantly lower cost at some point in the future. Once that happens those things can be regarded as utilities like electricity. I don’t think that there is any news in this that’s been the general trajectory for some time, the unknown is the speed and nature of that shift. Gartner is going for 2022 by which they are really saying is something like “within around 5 years”.

(One of the things that you need to understand about Gartner is that people listen to them, so when they report something it’s worth taking note even if it’s just to understand where a Gartner reader like CIOs and CTOs may be coming from in the future.)

Interestingly that electricity utility thought is also one of the key points raised by Stowe Boyd in A Q&A with Erica Morphy where he quotes Andrew Ng as saying “AI is the new electricity”.

To further underline that thought both ServiceNow and Grammerly made AI related announcements. ServiceNow are focusing their AI attentions on the automation of work. Grammerly is raising money to help augment our language skills.

Oh, and also, Amazon released another personal assistant based on Alexa, the Echo Show. This time Echo has been given a screen.


Gartner Says Artificial Intelligence Could Turn Some Skilled Practices Into Utilities

“The economics of AI and machine learning will lead to many tasks performed by professionals today becoming low-cost utilities,” said Stephen Prentice, vice president and Gartner Fellow. “AI’s effects on different industries will force the enterprise to adjust its business strategy. Many competitive, high-margin industries will become more like utilities as AI turns complex work into a metered service that the enterprise pays for, like electricity.”


A Q&A with Erica Morphy

“we have to learn to dance with the robots, not to run away from them. But that means we have to develop AI that is dance-withable, and not unrunnable-away-from.”


ServiceNow launches machine learning, AI automation engine

The four main use cases for ServiceNow’s automation efforts include:

  1. Anomaly detection to prevent outages in IT departments. ServiceNow will apply algorithms to find patterns and outliers that can lead to an outage. Anomalies can also be correlated with past events and workflows.
  2. Routing and categorizing of work. Learning algorithms will automatically route work based on past patterns. Tasks such as assessing risk, assigning owners, and categorizing work will be automated.
  3. Performance predictions. The Intelligent Automation Engine can be used to set a performance goal and data profile and get predictive analytics on hitting goals.
  4. Benchmarks vs. peers. ServiceNow is using the automation engine to compare companies to their industries and peers to gauge efficiency and make recommendations.

Grammarly raises $110 million in its first ever funding round

The company’s pitch centers on its machine learning capabilities. It claims this technology can dig into the substance of users’ writing in a way that’s not possible with Microsoft Word or other autocorrect programs.

Grammarly says it can advise not only on proper grammatical structure but on tone and word selection as well.


Amazon’s ‘Echo Show’ Gives Alexa the Touchscreen It Needed

Humans and Robots: Large Scale Changes from Many Smaller Scale Changes

The Institute for Public Policy Research Scotland has been looking at the impact of automation on employment in Scotland. Their estimate is that 46% of jobs are at high risk of automation. They also identify the primary challenge with this shift as being people’s ability to gain new skills whilst in employment, mid-career.

It’s not at all clear whether human skills can change at a rate that will allow us to outpace AI skills. There are differing views (see also Humans and Robots: Skills, Manufacturing and Construction) on this but I’m not sure we’ve got any choice but to try.

Many societies has been through these changes before, but not at this scale or this pace.

Whilst large changes are being predicted, the big shift will be made up of millions of smaller changes. One example of this are the Artificial Intelligence integrations that Microsoft are making in Microsoft Office. From design advice in PowerPoint to the Focused Inbox in Outlook these automations will soon become second nature to how we work. You’re already dependent upon the AI in the spelling and grammar capabilities. Driving all of these enhancements is AI that Microsoft is training with the data from over 100 million Office 365 users.

Also, there’s a little word from Dilbert at the end.


Automation poses a high risk to 1.2m Scottish jobs, report says

It put forward the recommendations in its Scotland’s Skills 2030 report, which said: “The world of work in 2030 will be very different to that in 2017. People are more likely to be working longer, and will often have multiple jobs, with multiple employers and in multiple careers.

“Over 2.5 million adults in Scotland (nearly 80%) will still be of working age by 2030. At the same time, over 46% of jobs (1.2 million) in Scotland are at high risk of automation.

“We will therefore need a skills system ready to work with people throughout their careers.


Microsoft and Artificial Intelligence’s long relationship is about to deepen


Humans and Robots: Skills, Manufacturing and Construction

At humans we are pretty good at falling into the trap of believing that what is has always been. We simplify the complexity around us by treating as many things as possible as permanent. Many of the macro systems which define our lives every day are not as permanent or historic as we treat them.

The idea of going out to a job is only a couple of hundred years old.

While Capitalism has been around since the 14th century; industrial capitalism has only been around since the 18th century.

People’s skills, and the way that they gain those skills, changed dramatically through that time. The skills we are going to need for the Robot future are likely to be very different to the skills we need today, that almost certainly means that the way we gain the skills will change dramatically also. But the big question is, will the Humans be able to keep up? In today’s Humans and Robots we look at some research by the Pew Research Centre debating the skills future.

We’ll also look at some of the areas already being impacted by the rise of the Robot:


The Future of Jobs and Jobs Training

As robots, automation and artificial intelligence perform more tasks and there is massive disruption of jobs, experts say a wider array of education and skills-building programs will be created to meet new demands. There are two uncertainties: Will well-prepared workers be able to keep up in the race with AI tools? And will market capitalism survive?

This report picks up on five major themes for skills and training in the emerging technology age:

  • Theme 1: The training ecosystem will evolve, with a mix of innovation in all education formats
  • Theme 2: Learners must cultivate 21st‑century skills, capabilities and attributes
  • Theme 3: New credentialing systems will arise as self-directed learning expands
  • Theme 4: Training and learning systems will not meet 21st‑century needs by 2026
  • Theme 5: Jobs? What jobs? Technological forces will fundamentally change work and the economic landscape

There’s a phrase that I’ve used a number of time on this blog: “Learning is work, work is learning” Harold Jarche. This is going to remain true for the present, and ever more so into the future, but it’s not clear that we will keep up, I’ll leave you with this thought:

About a third of respondents expressed no confidence in training and education evolving quickly enough to match demands by 2026.

Via Stowe Boyd – Forty Acres and a Bot


Apple’s $1 Billion Manufacturing Boost Will Likely Bring Robots, Not Factory Jobs

As we’ve explained in the past, advanced manufacturing—with all of its automation and super-efficiencies—can certainly bring productivity gains. But it won’t bring back manufacturing jobs. Just last month we finally got some hard numbers on the impact of automation on the labor force in our factories and warehouses: more robots bring with them decreased employment and lower wages. So if Apple’s focus is indeed going to be on using robotics, it’s not going to be good for the workforce.


MIT’s giant mobile 3D printer can build a building in 14 hours, and some day it may be headed to Mars

It might be targeted at Mars, but why not on Earth?

Humans and Robots: Automating the Buses

We are, apparently, entering a new era of automation and robotics.

For some this new era is one of opportunity where we explore new horizons with the help of robots.

For others the new horizon is one where we are beholden to our robot overlords.

I’m not sure anyone really knows the answer to where it will all end up predicting the future is notoriously tricky to do. So, I’ve decided to start curating some of the content I am seeing coming through and providing my own perspective on that content as a learning activity for me, and hopefully for you also.

I’m using the term robots to encompass anything that automates something that a human currently does, hence the title Humans and Robots.

As an example, from today:


The wheels on the self-driving bus go wherever they’re programmed to

Proterra, an electric bus manufacturer, just announced its three-phase plan to create the self-driving public transit system of the future, filled with autonomous, emission-free electric buses. The company says the move to autonomy should make mass transit safer and more efficient than ever before.

The automation of transportation is picking up pace with lots of very large organisations already committing significant investment budget. We have become used to autonomous trains in various situations, moving to autonomous buses is a significantly more complicated if those buses are to use the same road infrastructure as human drivers.

The days of driverless buses aren’t that far away, Proterra estimate 2019. That would have a significant impact on UK employment figures; Transport for London operates over 8,000 buses, as an example, I suspect that means that they employ over 16,000 drivers but I couldn’t find any definitive numbers. That’s a significant resource to redeploy in a transitional period that could be as short as 10 years. There will be some residual work for these drivers in cities like London where the tourists will pay for a heritage experience, but that’s a very small number compared to the needs for mass transport.

Whilst the impact on human employability is significant, so is the impact of safer emission-free mass transit. Many cities are struggling with air quality and what’s not to like about improved safety.