"Shaped like a Blogg! or a Garden hose!"

Artificial Intelligence, Machine Learning, Cognitive Computing, Deep Learning, etc. all seem to point to essentially the same thing: Computers being able to do perform tasks in a way that we would consider them smart.

Watching my children interact with Google Home got me thinking about how the technology is progressing and the future of work.

1. How our expectations of technology grow quickly; and
2. the legal and ethical issues that can come.

As background, recently I was in the US and was given a Google Home Mini by a colleague with the challenge of building something cool with it. Watching the very quick evolution of the way that they interacted with it was a bit of an eye opener.

As you’d imagine, the initial steps were pretty timid…

• “Hey Google, play music.”;
• “hey Google, what’s the temperature”; and
• “Hey Google, tell me a joke”.

These were basic requests and asking for information about the now. Then they started to test it…

• “Hey Google, what the weather for tomorrow” and
• “Hey Google, play Fine Music FM”.

The latter getting my attention as they were able to connect to an internet radio service and start to stream music; I thought I’d locked it down to just Spotify and my selection appropriate music.

What really got me thinking was how they then started to mine the internet for information. This year they are working through some projects and so my 9yo and 7yo started asking  “OK Google, what is Malaria”.. “OK google, tell me more about the symptoms”… and finally when my 7yo says “Hey Google, you’re awesome” to which it replied “you’re pretty good yourself.”.

My 7yo turns to my wife and I and says, “I think she likes me!”.

Up until this point I was pretty certain that they knew it was a computer. They’ve interacted with Apple’s Siri a lot in the past, knowing it was a robot and even complained about the pronunciations and semi-robotic responses. The fact that the voice is fairly realistic, has great intonation and was responsive in a very human way truly had them baffled; signs of a well designed conversation. Even when we asked the same question via Google search on our phones and showed that it was just reading the first response, it was pretty hard to convince my 7yo that it was a robot.

Growth in Expectation

Seeing the expectation of the technology rapidly rise, going from a toy to a useable tool is dramatic. I’ve seen this in the past where a new piece of technology was deployed, when it was done well, the expectation of what is possible and what it should do can quickly outstrip the initial capability of the system.

The use of AI and Machine Learning, and having the experience learn from the interactions, is how we are able to take the initial experience and have it grow with our expectations. Sometimes this is training the system using captured information of interactions and correct responses to build the basis of the rules that the machine needs to create and the logic it needs to follow. Training AIs can be as simple as a dozen samples, like Google’s Dialogflow, or tens of thousands of samples. It tends to come down to the algorithm, the complexity of the task and the accuracy you need.

Garbage in and Garbage out: One of the biggest issues with learning algorithms is, garbage in and garbage out. The repositories that they use, be it the data sources or the training sources will ultimately affect the outcomes. Back when I was at IBM, building the training question and answer sets for a WATSON engine, required a lot of time and effort to ensure that each was validated and tested. Through triggering Applications in Google Home, I’m finding that some of the responses can be bizarre, especially if I was the one that tried to create the dialogue; nothing like my 3yo telling me that he want’s the story app I created to stop telling him his favourite story.

Legal and Ethical issues

AI has the huge potential to remove human error, introduce new levels of efficiencies, and by taking out the people, bring costs of delivering services down significantly. However, through learning algorithms, there is the risk in what is captured and how it’s used. Watching learning algorithms add to their repertoire is pretty amazing, but very quickly biases can creep in.

Learned Biases and the actions of intelligent systems isn’t a new problem, though the example I easily recall is Microsoft’s Tay becoming racist in under 24 hours and having to be taken offline. Putting guide rails on the algorithms and black-listing content and behaviours is some of how the behaviours are curbed, however, people always find a way to use things in unpredictable ways.

As with the example of how my 7yo interacted with the the AI assistant, very quickly AI will become indistinguishable from human interaction and people will make decisions and take action based on the recommendations or logic provided by AI. What should worry everyone is how misinformation, fake news and peoples agendas can shape the way people interact with and use the advice of these systems.

Today there are laws and guidelines being put in place in certain geographies to prepare for the ethical and liability issues that will eventually ensue. I tend to agree with Elon Musk’s view that there needs to be a lot more effort put into how we control and govern AI because it will quickly become a lot more complex and ingrained into society, moving past the novel toy of today.

My final initial thought is on Data Mining. How is what is going in being used? What’s being recorded? How much is being stored? who has access to it? what does this mean.

Each platform is different in how they capture, store and potentially re-use recordings of what you say or do. I love the idea of conveniently asking questions in natural language and being able to data mine the full depth of the Internet, but at what cost. I suppose we won’t really know until something bad happens.

For now it will stay a toy that is switched on when I want it and be where I can keep an eye on what my kids ask it.

Last week I was fortunate enough to attend the AIIA Government conference on “Navigating the Internet of Things”. This is the 4th year that they’ve run a Government specific conference for sharing experiences and educating people on what is happening in the industry, locally and globally in Government with Technology.

The conference was opened by the Honourable Malcolm Turnbull MP (Minister for Communications), who gave a great summary of the state of affairs with regards to the adoption of Internet technologies and how industry, on the back of initial Government stimulation, is thriving, constantly reinventing itself and driving innovation.

The major themes of the conference was transformation, transformation of cities and how we do things more efficiently, be it resource use, transportation or healthcare. It also reiterated that the emerging IoT world is very much a Digitally driven economic world.

Resource Use

One example used by Minister Turnbull was Water. Water Utilities loose 25-50% of water  due to leaks and due to the reactive nature repairs, are extremely costly to  repair – NICTA have created analytics on predicting what pipe is is most likely to fail and when, allowing for proactive maintenance, reducing the cost of the service. David Gambrel of NICTA explained how this approach was already being used on the Harbour Bridge reducing the cost of maintenance 10 fold.

Energy use and smart lighting that make up approximately 25-50% of government energy budgets, was the another area explored. The move to transforming lighting to smarter, LED based technologies has the ability to significantly reduce the cost and use of energy. One idea posed was the ability to equip smart lamp posts with ability to be charging stations, also creating an opportunity for governments and councils to offer charging to electric cars and create a new source of revenue.

Transportation

Another example of resource use is roads. In Australian cities, congestion on roads account for 4.26B working hours wasted, said Minister Turnbull. Connected vehicles for traffic management could solve some of this. One of the biggest hurdles to date is the getting real life data and not driver opinions. As the cost of sensors and integrated chips continues to drop, live monitoring of services becomes more feasible, especially when we include feeds from the likes of Google Traffic. Understanding how roads (as a resource are used)

Steve Leonard, Executive Deputy Chairman, Infocomm Development Authority of Singapore (IDA) presented the challenges of the Singaporean government and their approach to Transportation – how to use infrastructure more efficiently, In summary support adoption of smart cars to essentially allow them to be packed closer on roads, potentially doubling the capacity of the existing roads. This was supported by Susan Harris, CEO of Intelligent Transport Systems Australia who’s research suggested that up to 40% more cars could be put on roads if we had automated cars with smart telemetry capability.

Lutz Heuser, CTO for the Urban Institute presented his Institute’s Reference architecture for future cities (see below). This was part of a wider view that to be successful in  to create a new Government service Infrastructure of data streams and analytics – new utility provided by governments. Cloud based open and realtime.

Smart Cities Reference Architecture – Lutz Heuser, Urban Institute, 2015

Finally UBER’s Melbourne General Manager explained how IoT and the marketplace they created using that technology allowed them to extend and supplement the public transport system.

The real future of the connected city or “Smarter” city will have smart and autonomous vehicles, providing better use of existing transport systems, allowing for denser and more efficient use of vehicles on the already crowded routes. All enabled by sensors that feed large inter-connected systems that make sense of the data.

Healthcare

Again Steve Leonard, (IDA) explained the problem they have in Singapore. Urban density of approximately 8000 people per square kilometre, means that they are not only far more dense than Australia or the U.S. but that they need to make sense of the projected needs of the population with the real estate available. Singapore, like most have an ageing population- they are all living longer and birthrate is slowing – This change in demographic has caused them to look at the statistics of hospital stays. If you are over 65 you are likely to stay 30% longer in hospital – this has a huge impact on hospitals and the projected number of future hospitals needed to support the population. Given geographic and economic constraints Singapore cannot build hospitals as much as they need; nor could they staff them. Additionally their studies have shown that 20% of patients contributed to 80% of re-admissions. So how can they offload chronic care, focus on triage and emergency care? They’ve looked to technology. leveraging their fibre network reach (1GB to each home) and eHealth technologies with in-home care to offload.

Dr James Freeman, CEO of GP2U.com.au a Telehealth business delivering services in Australia via video-conference so patients don’t have to physically see a Dr. and can have scripts filled and ready for pickup from local pharmacy. With the proliferation of sensors and cameras in consumer devices, they are able to deliver some consultation services remotely, never having to physically see a patient. Dr. Freeman pointed out that that the adoption is slow to date and this is a combination of no financial incentive to take up these services and legislation being slow to catch up to technology. The financial incentive model is absolutely necessary as there is little chance people will use these services off their own back. I’ve recently seen with my father-in-law, being issued a blood pressure monitor from his health insurer. Each measurement is logged and set directly to the provider for them to track his health. He rarely does it as there is yet no incentive to do so, no lowering of his premium or rebate for his troubles.

Government as a Service – The new Utility

What all of these presentations and discussions showed was that the future for Government is providing data as a service. Today the DTO is working at improving the way government delivers services, with the end goal of speaking to customers as one public sector. Delivering services on common platforms. Data.gov.au will continue to be developed and invested in.

This view was echoed by Ros Harvey, Chief Strategist and Advisor for KEI and Sirca, Government as a platform is the future, getting the community to innovate on top of the services and data that government supplies. This was reiterated by Pia Waugh, department of finance, who has been working for years working towards the goal of “Government as an API” and creating the mashable government- making what Gov does more available regardless of agency or jurisdiction.

If the Australian Government can continue with the work that they’ve started it will be well on its way to making Australia the worlds leading digital economy, an aspiration of Minister Turnbull.

How to make IoT successful.

The resounding themes were integrity and security will be important as IoT proliferates. Security must be the foundation of any platform (Brian McCarson, Intel) and approached from an epidemiological standpoint (Turnbull). Using high level pattern analysis and large mass data analytics to see trends and changes in the system.

Fundamental Tenants of IoT, Intel, 2015

Conclusion

IoT is breaking through the novelty and into the mainstream with the backing and support of Government. As more and more sensors find their way into roads, waterways, infrastructure components and government systems, this data, raw and refined, will become the new economy that governments will not only collect revenue from, but use to manage and shape the policies of the future. Using this knowledge and mapping the ILC cycle will help businesses (and government) understand how to leverage the innovation and properly commodities the services needed.

Today is a based off several things colliding at the same time for me – discussions with friends, colleagues and some twitter banter.

Everywhere I’ve been, risk management is broken into discreet units and managed individually ostensibly due to it’s complexity, working on the assumption that what they have is enough. Even Enterprise Architecture Frameworks skip over how Risk Management is to be engaged and offer little to no support in understanding the holistic picture.

Despite the argument of organisations that they don’t believe enterprise risk management (ERM) is necessary or that the existing static, compliance based tools or technique employed are sufficient, there is a place for ERM. By assuming that the nature of the business will stay the same, as-good-as-it-gets is an arrogant disregard for the fact that environments change. There will always be a requirement to navigate risk in business, as to avoid risk is to avoid success.

• How do you navigate risk in your business?
• Do you use a spreadsheet compiled from compliance questions?
• How about a pre-canned register provided by a consulting company?
• Is risk management handled at a project or programme level without higher level visibility within the organisation?
• Is there a single, unified view of risk management?

To disregard risks that may destroy value, you risk destroying the business; this is what static, disaggregated risk management techniques can cause. ERM, that is looking holistically at the organisation, provides a structured and disciplined process that aligns strategy, process, people and technology in order to maximise the desired outcomes and minimise the undesirable.

A holistic ERM approach allows the identification of various types of risks, providing the necessary visibility to the business. This visibility can provide the business with the ability to apply a measured and complete approach to the remediation or mitigation of risks, through tools and techniques, as well as identifying emergent risks to the organisation. As an example, a change in one area of the business’ policy due to legislative change, may have further implications though if handled in isolation, wouldn’t allow the business to be proactive.

Focusing on a single component of risk, such as looking to insure as a loss reduction technique for operational and financial risk, neglects the other risk types (of Technical, operational, financial, commercial or project-based/time based) and has the same affect as a business silo risk management model.

Read more…

 In IT and IT Security there is a constant complaint about the risks of shadow IT, and the adoption of consumer collaboration and sharing tools. Over the last couple of years we also saw the emergence of novel exfiltration techniques including the persistent ultrasonic technique, where the infected devices  communicates with other compromised hosts via high frequency; or the Twitter based technique, where malware sends out data 140 characters at a time for anyone to read;  and the more recent Video technique, encrypting data in video files and putting corporate secrets onto video sites or later retrieval.

Read more…

Warning, today is a bit of a rant. I had an email and chat exchange with a friend that wasn’t treated well recently and felt compelled to ramble.

Ethics is extremely important in business as it is the foundation of relationships. Ethics in the IT business is especially important as members of the Technology team(s) are responsible for representing IT to the wider business. Through the relationships IT builds with the business it is able to better understand the needs of the business itself and can develop real value through the strategic use of IT, using the collective smarts (IP) of the team. The Technology teams inside an organisation supports the business’ strategy, balances the wider strategic needs of the organisation and business units with the explicit needs of IT and IT strategies. Unethical behaviour can destroy this.

Let me be clear, when I say unethical I mean behaviour that isn’t:

• Honest;
• Courteous;
• Done with Integrity;
• Performed Efficiently; and
• Respectful of Property

Our individual actions ultimately reflect our ethical beliefs.When we are in a position of authority these also shape the way those around us operate.

The consequences of unethical behaviour in our IT teams is that it breaks the relationships, both internal to the team and the external ones to the organisation. This can cause team-members to become disconnected and jaded, holding back the IP that could make a difference between completing that aggressive project on time, creating that innovative new product or demoralise the wider team around them. The greater flow on affect is that IT will become disconnected from the business (again) and relegating it to that group that just cost a lot of money and doesn’t deliver anything.

It is easy to be dismissive in the heat of corporate action, but let’s face it, for the most part corporate IT is not life and death. Take the extra minute to think about the repercussions of the decisions you make and the actions you take, it may mean the ultimate success or failure for the perception of IT in the business.

/rant.

OK I think I’m prepared for that Ethics section in today’s exam!