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Is AI the End of Jobs or a Beginning?

Artificial intelligence (AI) is advancing so rapidly that even its developers are being caught off guard. Google co-founder Sergey Brin said in Davos, Switzerland, in January that it “touches every single one of our main projects, ranging from search to photos to ads … everything we do … it definitely surprised me, even though I was sitting right there.”

The long-promised AI, the stuff we’ve seen in science fiction, is coming, and we need to be prepared. Today, AI is powering voice assistants such as Google Home, Amazon Alexa and Apple Siri, allowing them to have increasingly natural conversations with us and manage our lights, order food and schedule meetings. Businesses are infusing AI into their products to analyze the vast amounts of data and improve decision-making. In a decade or two, we will have robotic assistants that remind us of Rosie from “The Jetsons” and R2-D2 of “Star Wars.”

See also: Seriously? Artificial Intelligence?  

This has profound implications for how we live and work, for better and worse. AI is going to become our guide and companion — and take millions of jobs away from people. We can deny this is happening, be angry or simply ignore it. But, if we do, we will be the losers. As I discussed in my new book, “Driver in the Driverless Car,” technology is now advancing on an exponential curve and making science fiction a reality. We can’t stop it. All we can do is to understand it and use it to better ourselves — and humanity.

Rosie and R2-D2 may be on their way, but AI is still very limited in its capability, and will be for a long time. The voice assistants are examples of what technologists call narrow AI: systems that are useful, can interact with humans and bear some of the hallmarks of intelligence — but would never be mistaken for a human.  They can, however, do a better job on a very specific range of tasks than humans can. I couldn’t, for example, recall the winning and losing pitcher in every baseball game of the major leagues from the previous night.

Narrow-AI systems are much better than humans at accessing information stored in complex databases, but their capabilities exclude creative thought. If you asked Siri to find the perfect gift for your mother for Valentine’s Day, Siri might make a snarky comment but couldn’t venture an educated guess. If you asked her to write your term paper on the Napoleonic Wars, she couldn’t help. That is where the human element comes in and where the opportunities are for us to benefit from AI — and stay employed.

In his book “Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins,” chess grandmaster Garry Kasparov tells of his shock and anger at being defeated by IBM’s Deep Blue supercomputer in 1997. He acknowledges that he is a sore loser but was clearly traumatized by having a machine outsmart him. He was aware of the evolution of the technology but never believed it would beat him at his own game. After coming to grips with his defeat, 20 years later, he says fail-safes are required … but so is courage.

Kasparov wrote: “When I sat across from Deep Blue 20 years ago, I sensed something new, something unsettling. Perhaps you will experience a similar feeling the first time you ride in a driverless car, or the first time your new computer boss issues an order at work. We must face these fears in order to get the most out of our technology and to get the most out of ourselves. Intelligent machines will continue that process, taking over the more menial aspects of cognition and elevating our mental lives toward creativity, curiosity, beauty and joy. These are what truly make us human, not any particular activity or skill like swinging a hammer — or even playing chess.”

In other words, we better get used to AI and ride the wave.

Human superiority over animals is based on our ability to create and use tools. The mental capacity to make things that improved our chances of survival led to a natural selection of better toolmakers and tool users. Nearly everything a human does involves technology. For adding numbers, we used abacuses and mechanical calculators and now have spreadsheets. To improve our memory, we wrote on stones, parchment and paper, and now have disk drives and cloud storage.

AI is the next step in improving our cognitive functions and decision-making.

Think about it: When was the last time you tried memorizing your calendar or Rolodex or used a printed map? Just as we instinctively do everything on our smartphones, we will rely on AI. We may have forfeited skills such as the ability to add up the price of our groceries, but we are smarter and more productive. With the help of Google and Wikipedia, we can be experts on any topic, and these don’t make us any dumber than encyclopedias, phone books and librarians did.

A valid concern is that dependence on AI may cause us to forfeit human creativity. As Kasparov observes, the chess games on our smartphones are many times more powerful than the supercomputers that defeated him, yet this didn’t cause human chess players to become less capable — the opposite happened. There are now stronger chess players all over the world, and the game is played in a better way.

See also: Microinsurance? Let’s Try Macroinsurance  

As Kasparov explains: “It used to be that young players might acquire the style of their early coaches. If you worked with a coach who preferred sharp openings and speculative attacking play himself, it would influence his pupils to play similarly. … What happens when the early influential coach is a computer? The machine doesn’t care about style or patterns or hundreds of years of established theory. It counts up the values of the chess pieces, analyzes a few billion moves, and counts them up again. It is entirely free of prejudice and doctrine. … The heavy use of computers for practice and analysis has contributed to the development of a generation of players who are almost as free of dogma as the machines with which they train.”

Perhaps this is the greatest benefit that AI will bring — humanity can be free of dogma and historical bias; it can do more intelligent decision-making. And instead of doing repetitive data analysis and number crunching, human workers can focus on enhancing their knowledge and being more creative.

5 Predictions for the IoT in 2017

The IoT continued its toddler-like growth and stumbles in 2016. Here are five trends to look for in 2017 as the IoT enters its adolescence and how to benefit from them.

1. Ecosystems begin to determine winners and losers

Previously these were nice in-the-future concerns; now they will really count. Filling out a whole product value proposition through partnerships has repeatedly proven its importance across B2B and enterprise software sectors. In the IoT, they will be even more critical.

As an example, the Industrial Internet Consortium (IIC) is driving the definition of platforms and test beds and should show results in 2017. In the meantime, expect some IoT companies to fail when they can’t gain traction.

If you’re developing IoT infrastructure or platforms, it’s time to get real, regarding building great partnerships, developer programs, tools, incentives and joint marketing programs. Without them, your platform may appear like an empty shopping mall.

If you’re a device manufacturer or application developer, it’s time to place your platform bets so you can focus your resources. If you’re implementing IoT-based systems, you’ve been through this before. Welcome to the next round of the industry’s favorite game, “choose your platform.” Make sure you also evaluate vendors based on their financial health, business models and customer service — not just technology. Learn more in Monetizing IoT: Show me the Money in the section “Ecosystems as the driver of value.”

See also: Insurance and the Internet of Things

2. Vendors get serious about experimenting with business models and monetization

This was a big theme at Gemalto’s recent LicensingLive conference and was further driven home by solution partners like Aria Systems. Tech won’t sell if it’s not packaged so that buyers want to buy. Look for innovation in business models and pricing, including subscription models, pay per use, recurring revenue, subsidization or replacement of hardware device revenues with service revenues, monetizing customer data and even pay-per-API call models. If you’re marketing whole solutions, be sure to avoid the “partial solution trap” as described in my article, The Internet of Things: Challenges and Opportunities.

3. Big Data gets “cloudier” (pun intended)

No doubt there will be a lot more data with billions of new connected devices. Not just text and numbers but also images, video and voice can all add significant monetization opportunities to different participants in the value chain. More devices mean more data, more potential uses and more cooks in the kitchen. This is a complex cluster of issues: Do not expect a resolution of ownership, privacy or value in 2017.

Instead, approach this by building a clear vision of what you want and don’t want with respect to data rights as you enter these discussions. And try to anticipate the genuine needs of your partners. Device manufacturers will likely have a going-in desire to own data produced by their devices; and apps developers, the data they handle; others may be okay with aggregated info. Buyers should make sure they understand what’s happening with their potentially sensitive data. We have already started to see partnerships and deals stall out over intense discussion on data ownership and rights.

4. You’ll need to prove your security, with privacy not far behind

2017 IoT systems are going to need to up their game. No one is going to stand for hacked doorlocks, video cameras or Mirai botnet/DDoS attacks via connected devices much longer. Similar events will come with very high price tags. So far, the IoT has dodged any major incidents with large losses suffered directly by end users.

We could see growth flatten if a major hack of thousands of end users occurs in 2017, especially if hardware devices are ruined or people get hurt. At that point, users will need to receive greater guarantees of security, privacy and integrity. This risk needs to be mitigated if the industry wants to avoid an “IoT winter.”

Vendors will need to invest more in security development and testing before deployment and offer assurances, possibly including insurance. Installers and integrators will need to ensure ecosystem integrity, and buyers will look for these guarantees. Just one flaw could be very expensive: Gartner believes that by 2018 20% of smart buildings will suffer digital vandalism through their HVAC, thermostats and even smart toilets.

5. Voice-powered, AI virtual assistants drive a next round of platform wars

Voice will become increasingly important to control IoT systems and computing infrastructure. Google Assistant, Apple Siri, Amazon Alexa, Microsoft Cortana and Samsung’s Viv Labs acquisition underscore the importance of these new AI-assisted voice interfaces. They’ll be used across multiple devices like phones, PCs, tablets, cars, home appliances and other machinery. By 2020, Gartner believes smart agents will facilitate 40% of mobile interactions. This is the beginning of a new round of platform battles that you need to recognize, internalize and prepare for.

See also: How the ‘Internet of Things’ Affects Strategic Planning

What do you think? Email me with your predictions, comments or war stories.

You can find the original article here.