Top Reads on AI
Whilst I love to read, our series of lockdowns in Victoria has given me more than ample time to add quite a few titles to this year’s reading list. I have also taken to audio books on my daily walks within my 5km zone! So we have compiled a short list on our top reads on ai at Red Marble.
It is not an exaggeration to say AI is a hot topic in Australia and globally right now and it’s the key to our business.
So let me draw your attention to a few great reads.
Here are my top 4 at the moment my other favourite top reads on AI for business leaders are:
- The AI First Company by Ash Fontana
- Atlas of AI: Power, Politics and the Planetary costs of Artificial intelligence by Kate Crawford
- Competing in the Age of AI by Karmin R Lahaina and Marco Iansit
- Human Compatible: AI and the Problem of Control, Stuart Russell
So let me dig into one particular gem: The AI First Company.
Ash Fontana is an internationally-renowned startup investor and venture capital partner of Zetta Capital.
Known as a trailblazer even in San Francisco, in The AI First Company he’s produced a great playbook for those providing AI services or looking to use AI to increase productivity in the workforce. It is a first to see this information all in one space, and is a critical guide for businesses building product or consulting in this space.
It’s honest. It talks about the pitfalls as well as the opportunities (of which there are many).
This is important. As we see across Australia, AI is still often at risk of misunderstanding and fear-mongering amid valid concerns around privacy, bias and noise in its implementation.
Ash Fontana has recently said while there is a long way to go for Australia to become leaders, Covid-19 has produced a kind of reverse brain drain with top talent moving back to Australia to ride out the pandemic.
For AI businesses
In his book Fontana outlines the differences between AI product and consulting businesses. People think it’s easy to move from consulting to building a SAAS product but as he clearly outlines, you need different motivators.
He says they’ve been co-existing but now they are splitting and becoming more defined in their own right.
AI First is a guide in self education of the different models these businesses are employing which will be useful for AI teams, as well as product management and technical teams.
For companies looking to introduce AI
While AI has been really exploratory, it has now become really clear the advantages that it gives organisations and leaps they can make by building it into their ways of working.
It’s not a pipe dream.
What we are seeing is how quickly those that do use AI effectively get ahead. Consumers are exposed daily to the effects of AI for example the influence on their purchasing habits of algorithms.
The challenge is that while it is essential I don’t think we should be leading with just AI anymore.
What organisations will increasingly need is engineering and product managers to embrace machine learning and AI as just part of the toolkit.
Companies will need specialists to help organisations with the deep knowledge to create experiments and accelerate their learning. While we are building talent, to go it alone in-house now will be a slow burn, what is proving more effective will be to inject clear competency for short medium term through external sources.
For everyone
The crux of this book reinforces our thinking at Red Marble. AI is no longer the bleeding edge, it has moved beyond theory. Experts can now introduce and implement AI quite easily but it is still perceived as a hard thing. It is not.
Ash Fontana’s book makes this really clear with a guide to how this can be achieved. It is essential reading for any companies in AI and all Australian business leaders.
Happy Reading
Sifting the noise: what do Nobel-prize winning author’s new book and AI have in common
Sifting through “noise” in AI is like creating the perfect slice of your favourite cake. First you need to bake the cake, which requires careful preparation, great ingredients and the right equipment.
I love cake! And even if you don’t, I think it is a great analogy for how to approach this new technical opportunity with AI.
It has long been the promise that technology will elevate us, that it will help us make better, fairer, more humane decisions that save lives, money and time.
Technology, specifically AI now has the power to do this.
But it is how we apply it, how our leading companies deploy it within their workforces, and how boards and executives take the time to understand complex technology, that will lead to lasting change.
Using AI algorithm-based decision-making – to make or inform decisions has become a politically charged endeavour, with focus rightly on its flaws, including human led bias in creating the algorithm. However, people, even those with significant expertise, as it turns out, are quite often poor decision makers.
“Unfortunately, decades of psychological research in judgment and decision making has demonstrated time and time again that humans are remarkably bad judges of quality in a wide range of contexts,” Alex P. Miller writes in the Harvard Business Review.
“Thanks to the pioneering work of Paul Meehl (and follow-up work by Robyn Dawes), we have known since at least the 1950s that very simple mathematical models outperform supposed experts at predicting important outcomes in clinical settings.”
Along with an all star team, renown psychologist and Nobel-prize winning Daniel Kahneman, has released a new book, Noise, which should be essential reading for all Australian executives.
Kahneman and his co-authors have outlined the difference between “bias” (systematic deviations) and “noise” (random scatter), and how both, but particularly the latter, affect decision making in the business world.
It is bias that has taken much of the focus, however it claims that noise creates as much if not more damage.
“Controlling noise is hard, but we expect that an organization that conducts an audit and evaluates the cost of noise in dollars will conclude that reducing random variability is worth the effort,” Professor Kahneman writes in the Harvard Business Review.
Intelligent use of technology is integral to this, so where to start?
But first let them eat cake
Using technology like AI to sift through the noise and enhance decision making requires a different way of thinking. Red Marble believes in the medium term, “AI” will become less of a headline, and become a standard part of the devops suite.
However, in the short term, AI is expanding for all sorts of potential use cases to filter through the noise.
Which brings us back to our favourite slice of cake. A delicious, sometimes simple, sometimes more complex baked product, used for specific occasions.
To make the cake, first you also need the ingredients – the inputs – and the recipe – the methodology.
A truly skilled baker will also know just how long before starting to take the butter from the fridge, then to cream the butter and the sugar till it is perfectly smooth before sifting in the flour.
They will understand the variables of their oven to ensure a perfectly timed bake, and they will know to let the cake cool before they put the icing on top. The baker, and the creator of the recipe are both important, the former understands the higher the quality of inputs, the better the cake will be and the latter has experimented to find that perfect process.
To get that end result – the output – or the perfect cake, takes time and multiple tries. When did you learn a new skill like surfing or swimming without practice?
Filtering the noise
Increasingly AI is being used to make decisions, or provide the information, instead of humans.
Noise looks at how our systems are broken and how being overly reliant on people can create increasingly flawed outcomes. It uses case studies, research and statistics to spell out its arguments.
Inherently systems are broken when two professionals, in the same company make different decisions based on the same information.
This is where AI can improve outcomes. It is where we can begin to really “refine the recipe and bake the cake to perfection”.
Where is this going?
For Australian boards, executives and companies, it is essential to acknowledge the limitations of people in key decision making roles, and begin to understand how technologies can support employees in not just making better decisions, it will lead to improved productivity when paired well.
In any industry there is noise. The “Cake” or the AI-led technology in most cases is not in the realm of science fiction.
It is simple. It is machine-learning based decision making.
At Red Marble we have many examples of where clients across many industries have used AI algorithms to eliminate silos and blind spots to add value to the bottom line.
Ultimately, for executives looking to understand why and how AI can be used to improve their organisations, Noise will become one of 2021’s essential and most influential readings.
‘Noise may be the most important book I've read in more than a decade. A genuinely new idea so exceedingly important you will immediately put it into practice. A masterpiece’
Angela Duckworth, author of Grit
‘An absolutely brilliant investigation of a massive societal problem that has been hiding in plain sight’Steven Levitt, co-author of Freakonomics
And if all this has made you hungry… here are some baking tips.
Does the Budget put innovation in Australia behind?
“Innovation is the most important thing to Australia going forward.”
I wholeheartedly agree with SpeeDx’s Dr Alison Todd on the patent box announced in last week’s Federal Budget and join her in urging for it to be expanded out of health and biotech.
The Budget has made both winners and losers of companies leading innovation in Australia.
The Government has lauded its own digital strategy and “investment” into the future for Australia. Prime Minister Scott Morrison said: “Australia has led the world with innovations like Wi-Fi, the bionic ear and a vaccine for cervical cancer. We want to see more innovation commercialised in Australia.”
The Opposition appears to agree with Labor leader Anthony Albanese making innovation in the form of support for training and a “Startup Year” for university students a key part of his budget reply to encourage new businesses and innovative thinking.
They are right to think this way. Innovation is not just a buzz word for tech boffins, it has practical implications for jobs, businesses and economic growth. It is an important conversation that we need to have right now to continue to educate our leaders.
We are still underinvesting in AI
But the budget itself only goes part of the way towards addressing this. The US, while a far larger country, is set to invest $6 billion into AI this year alone, by comparison in this budget Australia has increased its spend to $124 million over six year. This is just half of what the industry is calling for.
We need access to overseas talent
As the world emerges from the pandemic, we still lack access to overseas talent. Our borders are unlikely to open until next year and with recruitment in technical roles already difficult, this will increase the fight for talent.
But ESS will help us retain talent
The changes to employee share schemes, where tax will no longer be payable on shares when an employee leaves the business, will help encourage take up of this scheme.
This artificial taxing point in many cases forces the former employee to sell the shares to meet the tax liability and acts as a deterrent.
Patent and software write downs will help
There are more positives for the tech industry. The new patent and continued software write-downs will go some way to encouraging uptake of innovation and allow companies more ability to experiment.
As accountants have advised, the current rules have become outdated and are not keeping pace with what happens in reality, especially with software.
At the moment if you acquired a patent, you would need to claim the cost of that patent over 20 years.
Under the new rules, you will be able to self-assess the actual effective life of that patent and instead claim the cost over those years.
This same rule will also come into effect with in-house software in July 2023. What that will mean is that if it’s going to be obsolete in two years then you now claim over those two years.
What we really need
Kickstarting an “innovation boom” isn’t just a tech issue - this affects every industry from construction, medicine to finance.
Red Marble works in depth with industries including construction and infrastructure, so seeing strong investment into these sectors in the Federal Budget is encouraging.
Australia’s politicians have been cautious of overtly supporting the emerging tech sector and the optics of creating tech billionaires.
Our concern is politics getting in the way of the opportunity created by the current pandemic and its recovery on a global scale.
In its reply Labor has criticised the Government for making this a pandemic patch-up budget rather than a committed plan for Australia’s future.
Waiting years to invest in artificial intelligence, technology and supporting emerging companies in Australia may end up putting us further behind the rest of the world.
We need to open more conversations with our leaders so they can understand what is truly at stake in this budget and beyond. Aren’t we already far enough behind?
COVID-normal, powered by AI technology: the perfect storm
Futurists have long predicted that AI technology will leave a lot of workers without a job - especially those with specialised skills. As we emerge from a global pandemic and settle into ‘COVID normal’, the big question is: can AI help people get into work, rather than the other way around?
The answer is yes - however there is a ‘but’. It’s summarised well by a quote in this Wired article:
“You’ll be paid in the future based on how well you work with robots.”
There are many examples of humans and machines complementing each other, but it’s important to remember that we excel at different types of skills. Humans should focus on skills that they uniquely enjoy exercising, while AI technology handles the mundane tasks that don’t require human skills of judgement, creativity or empathy.
Humans and AI technology working together
International tech investor and startup adviser Anupam Rastogi describes the relationship between AI and humans as ‘human-machine symbiosis’.
In 2016 he wrote about the difference between artificial intelligence and intelligence augmentation, and mentioned examples from manufacturing, transport logistics, healthcare and agriculture where companies were leveraging advances in machine learning to augment human capabilities, enhance productivity or optimise use of resources.
Fast forward to today and many AI technologies have developed to help humans thrive, such as:
- Weather predictions helping farmers make real-time decisions on when to pick, plant and harvest.
- ‘Robot' vacuum cleaners that work away when you're not at home and free you up to do other things. This is a winner for me!
- The Australian born Swarm Farm Robotic is empowering farmers to automate their operations, even down to driving the tractor.
- And coming soon, you will see the use of prediction AI being used to help save lives by predicting natural disaster events.
How much is AI technology worth to economies?
A recent article in the Australian Financial Review predicts that the COVID-19 pandemic could triple the value of AI, as businesses rush to digitise many of their processes.
Krishan Sharma, technology journalist writes:
“A government-sponsored road map from CSIRO published at the end of 2019 found that the AI sector would be worth $315 billion to the Australian economy by 2028 and $22 trillion to the global economy by 2030.
However, experts such as KPMG's Partner-in-charge, James Mabbott, tells the Financial Review that both these figures could be as much as “1.5 to 3 times greater” after taking into account the increased levels of investment driven by the disruption caused by the pandemic.”
There’s no doubt that the pandemic has helped push many businesses out of their comfort zone and into a place where they’re more likely to consider digital options and artificial intelligence. How the industry handles this increased interest - and spend - is crucial.
How AI technology is affecting jobs - now and in the future
One factor that will have a big influence on the success of AI’s broader adoption is the people currently employed to integrate it into workplaces. Right now AI is a growing industry - and it will only continue to grow. Having the right people leading AI programs is essential for ensuring that AI operates in harmony with the human workers in the business to generate sustainable positive results.
Infosys’ 2018 ‘Leadership in the Age of AI’ report revealed a possible expertise issue:
“Two thirds of Australian organisations are having difficulties in finding suitable staff to lead AI technology integration and 75% of IT decision makers felt that the executive team in their organization needs formal training on the implications of AI technologies.”
Looking forward, it seems inevitable that there will be some disruption to employment - but does the end justify the means?
The Adelaide University’s 2018 (yes, a little dated, but still relevant!) report “The Impact of AI on the Future of Work and Workers” concludes:
“Occupations that can be replaced by AI and robots will be vulnerable. This has been true for the last 200 years of technological innovation and is hardly a surprise. There is not much call for typists anymore. Nor horse husbandry. These jobs have been taken over by machines. No doubt AI will substantially replace some occupations. But we have also learned from history that despite ever increasing automation from machines such as engines and computers, the total amount of employment has increased and average wealth has increased remarkably.
The capacity of countries to adapt to greater automation has required retraining and investment in education and research on a mass scale so as to build the capacity of the workforce to make best use of the new technologies developed.”
People before profit
The driving force behind AI - as with most other trends or technologies - is money.
As interest in artificial intelligence grows, there is a strong focus on reducing the time and resource required to create machine learning models that can generate the opportunities which will enable the workforces of the future.
It’s in this scenario that the AI industry and humans can really thrive, as long as we find a way to strike the right balance between AI doing our jobs for us, and helping us do our jobs better.
Then comes the next set of questions that need answers:
- Where will the accountability lie to reskill?
- Will it be up to individuals to head back to the classroom, or create working opportunities to develop the required capabilities?
- Or will industries lead the way by putting humans before short-term profits?
If you’d like to let us know your thoughts, or find out more about what AI technology could do for your business, we’d love to talk. Please get in touch.
Post-COVID hack: Driving user adoption of digital technologies with AI
The hack is back!
At Red Marble, we’ve done some of our best work during short, focused hackathons that aim to generate an idea—and then develop it into a prototype—in just a matter of days.
As a company that helps clients incorporate AI into their business, these hackathons provide an incredible foundation from which we can solve real organisational challenges and improve the competitive advantage we can offer. It also helps us practice our skills in an artificially intense, fast-paced environment.
Over the last two years we’ve run successful hacks with a number of clients including Webjet, Coca Cola Amatil, Dulux, Bookbot and others.
We’ve also run a number of internal hacks where we split into teams and tackle a specific problem. However, this has been tricky of late due to the working from home rules.
In early June, using a combination of dispersed desks in the office, plus Zoom and Slack, we ran our first post-COVID hack!
Our team focused on how we can employ AI to better drive user adoption of digital technologies in corporate environments. This has become an important issue across almost all industries as our workforces move online.
McKinsey recently reported on the need to blend digital technology, analytics and behavioural science to personalise change programs. The article highlighted that the most effective way to make organisational change succeed is to carefully consider each employee's unique skills and mindset
It turns out there’s already some pretty impressive capability in the consumer world that can be applied in corporate environments. For example, the algorithm-based management of messages and communications that share what’s relevant and appropriate for every user, based on their individual capability and readiness.
A quick break from the hack for lunch with office dog Jimmy.
Many companies make large investments in digital technology with strong business cases, on the assumption that software is properly adopted by the users. In practice it doesn’t always work like that.
In a post COVID-19 world, this adoption has never been more crucial.
That’s why hacks like this one are extremely helpful. They give us a chance to test our hypotheses around what drives user adoption. By regarding each employee as a unique individual, we’re proving that we can reduce a business’ overall costs and realise the productivity potential of what these technologies offer.
As a result of our recent internal hack, Red Marble is excited to be piloting solutions with two clients. We’re using AI algorithms to tailor unique messages to each individual and drive process adoption - effectively automating organisational change.
We’ll report back on the results, what we learned and how the power of AI can improve user adoption of the many technologies being implemented across organisations.
If you’re struggling to drive user adoption of your big technology purchases, need help with change or can see other areas for optimisation, AI can help. Get in touch - you never know, we could be solving your problem at our next hack!