The Data Debate
Robot Visions by Isaac Asimov

The Data Debate

In our lifetimes it’s a robotic Sci-Fi future…


I grew up reading Isaac Asimov science fiction novels which have had a direct influence on the way I feel about the evolution of technology, even to this day.?

Many people fear the progression of advanced, independent self-reasoning robots, but Asimovs’ three laws of robotics proposed a level of governance that made them seem friendly, non-threatening and helpful:

1 - A robot may not injure a human being, or, through inaction, allow a human being to come to harm.?

2 - A robot must obey the orders given to it by human beings except where such orders would conflict with the first law.?

3 - A robot must protect its own existence as long as such protection does not conflict with the first or second law.?

Although Asimov’s 3 laws were invented for his science fiction writing, I believe they are to be respected in today’s world of IT,? AI and robotics. Especially when we have autonomous, reasoning, intelligent robots working alongside us in the not-too-distant future.


….but right now Data is the new Oil

At the dawn of 2020, WEF estimated the amount of data created daily in the world, at 44 zettabytes. That’s an insane amount of bytes of data. (21 zeroes worth in fact! Or 1,000,000,000,000,000,000,000 bytes worth).

The number pertains to the total amount of data generated each day by social media sites, financial institutions, medical facilities, shopping platforms, automakers, and many other activities online. And it’s an insane figure, whichever way you look at it.?

In fact, at the beginning of 2020, the number of bytes in the digital universe was 40 times bigger than the number of stars in the observable universe. By 2025, this figure will reach 463 exabytes globally.

Google, Meta, Microsoft and Amazon, each store over an exabyte of information - that’s 1,0006 bytes. And therein, lies their value. “Data is the new oil they say” - and it’s true because where there is data, there is wealth. But none of them started out with data collection as their goal. Amazon was selling books, Facebook was a place to connect with friends and post photos online. However, because they were tech companies from the get go, they ensured that data and analytics was a core part of their strategy.?


The Amazon Effect?

Collecting thousands of millions of data points over time, too overwhelming for any human to be able to even consider, Amazon has successfully leveraged AI and Machine Learning to analyze and understand customer behaviour. Using this insight to predict and forecast allows them to provide recommendations of what you might like to buy next. Through user behaviour insights, learning more about you, what you like and what others like you like, companies such as Amazon can predict what you want before you even know you want it. This therefore, is useful for us humans.?

Today, the company is an entire digital ecosystem in which you can buy and sell books, tech, clothing, groceries, anything at all, as well as find, test, buy and deploy third-party software for your business via AWS Marketplace. You can buy using their payment gateway and get protected online with Amazon Protect. You can connect your home and office into the ecosystem with smart devices that will turn the lights on and off, music, and power when it understands your daily rhythms. You can add things to your shopping list when the fridge runs low on something, and even head to an Amazon store in some parts of the world for groceries without needing to bring your wallet.?


Invasive, or productive??

Many people find this quite scary, which is understandable. Many people find it unnatural that companies seem to know our online behaviours better than we know ourselves. Some people still think that AI and ML will eventually replace us and there’ll be no jobs left for humans! But overall, the benefits for me personally, far outweigh the concerns.?

Out of the teams operating at Johnson Controls-Hitachi, I would say that my marketing team is one of the largest users of AI, ML and big data at the moment. We might use it to analyse the performance of our social media campaigns, aggregating thousands of data points across our marketing channels to identify what our customers are saying about certain products, and measure sentiment about their performance. Also known as Social Listening. We’re bringing all of our offline instruction manuals online to save paper, reduce waste and make it easy for customers to get access to what they need. Also known as Digital Transformation.? And AI will better enable us to gain insight by considering what pages or areas people are navigating to most on our websites, and allow us to tweak and refine them to answer the questions people need answers to most = improved CX.

Ultimately - we’re using it to save time both for ourselves and for our customers, to work out what they need most and what will be most helpful for them. There is nothing malicious or worrisome about that.?


Productive AI and ML

IOT devices like Alexa and Google Home make life easier, like turning on the aircon with a simple voice command, or simple home automation like our very own SmartFence technology that turns my AC on or off automatically as I approach or depart my house. These things just make life that little bit easier for me.?

All those moments saved by smart devices and automation of tasks add up to hours of extra time that I can use to get work done,? or add to my leisure time,? which in turn,? improves my quality of life. AI and ML helps my devices themselves optimise and adapt to the way I prefer to use them,? allowing me to be more efficient, and ultimately save me money in the long run too.?

Similarly, the way we use AI at Johnson Controls-Hitachi starts with the customer. The social listening tools we use for example, collect thousands of data points and help us to identify trends in what our customers are saying about our products in line with certain times of the year or new releases. We can use that to tweak and refine our messaging to make sure we’re answering the right questions when customers need them, or even pass on the insights to our design teams to reflect in our software updates and improve the next generation of products.

With IoT monitoring our hardware, we can identify and predict issues with our HVAC products, flag that it needs maintenance and schedule a service call before a part fails, thereby reducing downtime. This maintains continuity of service and helps keep everyone safe too which is so much better than the old fashioned way of break/fix.?


Where to draw the line

Automation and machine learning in my view, is easily adopted and best applied for simple, repetitive tasks or data modeling: assisting humans with making small decisions more efficiently, providing the information needed to be able to make them faster, removing friction and ultimately helping them do their jobs better. Where it becomes inappropriate or unsatisfactory, is when it’s being used to do something really complex without human involvement. My suspicions would be raised when it is being relied upon to actively make suppositions or hypotheses and then make decisions without a human touchpoint involved, especially where there is people’s lives or morality at stake.?

A mistargeted ad on social media, or a delay in processing time for a purchase order is one thing, but if a political party is targeting people in order to influence or push an agenda, and the future of a country’s governance is impacted… the implications are quite different. If a CAT scan is misread and someone gets misdiagnosed, there could be a life lost at the hands of a robot. And that is simply not acceptable.??


Artificial intelligence is artificial?

There is a reason why it’s called “Artificial Intelligence” not just “Intelligence”. It should not be mistaken for “Intelligence”, or “fact” and all of us have a responsibility to delineate how far we trust it and the actions we allow it to inform. AI does not care about morals or emotions, and that’s what separates robots from humans. AI must be used to assist people and facilitate humans making better decisions, especially when they are important. So this means when ML & AI assists humans to make decisions - it is productive and efficient. However when AI replaces humans and makes important decisions independently - this is risky and deserves concern.

I’ve explained why I am positive about the advancement of technology more generally and am in favor of drawing greater business intelligence with the increased sophistication of data collection. But with increased insight comes increased responsibility.?

Within Marketing, but this can apply as a general rule too - there are key questions we should be asking ourselves and asking them frequently, as a matter of principle:

  1. What is our starting point??
  2. What is the desired outcome??
  3. What will benefit the customer??
  4. What is at stake if we get this wrong?

This is an oversimplified approach, but sometimes simple rules, like Asimov’s 3 laws of robotics, are best followed.?

??Matthew C. Smith

Helping business growth through a strong brand message and local connections. Brand stylist, Graphic Designer. Human being and learning.

2 年

Whatever humankind achieves we should be aware of the possible consequences if how our decisions affect others and be accountable and prepared to face them. Pride cometh before a fall.

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Carl Geraghty

Going placidly amid the noise and the haste

2 年

Interesting food for thought, thanks for sharing

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