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At the 2017 Web Summit in Lisbon, when Sophia, a humanoid robot powered by artificial intelligence (AI), joked “We will take your jobs,” behind the nervous laughter of the 60,000 attendees was a realisation this could be a reality sooner than they think. The rapid pace of developments in AI has already begun to disrupt entire industries. While technology is helping replace antiquated systems with agile, innovative tools, it is also set to impact jobs and millions of people. While popular opinion from technophobes suggests machines will entirely take over our jobs, the truth about the future of jobs is a bit complex.

What will future jobs be like?

Technological advancements have had a direct impact on jobs, creating new ones and eliminating the redundant. Today, technology and digitisation have made the lives of consumers simpler, while enabling businesses to leverage advanced tools like AI and Machine Learning to build better products and services. A recent Gartner report noted that the next couple of years will be a defining period as AI will be a major job-creator.

The report stated that, by 2020, AI will generate 2.3 million jobs, exceeding the 1.8 million it is expected to replace. It also revealed that the number of new jobs created by AI and AI-powered tools will reach 2 million by 2025.

A large number of sectors and enterprises that have integrated AI are using the technology primarily for Big Data Analytics through Machine Learning tools. In the digital age, gigabytes of data are created each second by millions of consumers. In order to reach out to customers in a more efficient way, data-driven personalisation is a key element of effective customer service.

Hence, businesses are going to great lengths to ensure they are equipped to use this deluge of data to their advantage—for delivering a higher quality of services and products to customers, and staying ahead of competitors.

Thus, AI has come to play a critical role in key processes like sales and marketing. From powering recommendation engines of Google, Netflix, Amazon that push personalised content towards consumers, to performing complex functions like data and cybersecurity, financial trading and fraud detection, AI can perform a range of functions.

But the application of AI and Machine Learning is largely limited to functions like collecting and processing data, and hence a skilled human workforce is essential for creative tasks and roles that demand human skills, and qualities like emotional intelligence. As of now, less than 5% of occupations are entirely automated, and about 60% comprise 30% tasks that can be automated.

It’s more likely, then, that humans will continue to guide machines, and dominate jobs that require essential skills such as interpersonal relations, emotional range and complexity, dexterity, and mobility, as opposed to the idea that machines will make us redundant. […]

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In short, there is a global demand for clean, cheap, reliable energy – and artificial intelligence (AI) is increasingly being used to help meet this need. Enabling the growth of low-carbon, green electricity is an AI application with a potentially huge long-term impact. Enabling the growth of low-carbon, green electricity is an AI application with a potentially huge long-term impact Renewable forms of electricity are emerging as the successors to traditional coal and gas-fired power plants. A key problem with renewable electricit y, however, is its inconsistency. A cloudy day or a string of calm, windless afternoons will cut generation and can create power shortfalls. Conversely, too much energy can be generated; in March this year, for example, a sunny, windy Portugal produced more renewable electricity than it consumed.

At present, this means backup forms of power, which can be switched on quickly, often dirty diesel generators or coal plants, are used to smooth out the troughs and costly storage solutions are required to manage peaks of excess generation.

Using AI to forecast and make energy-saving decisions

Aidan O’Sullivan, head of University College London’s energy and AI research, says using AI to create “forecasts for electricity demand, generation and weather can lessen the need for these backup mechanisms”, by predicting and managing fluctuations in production.

AI research is also investigating decision-making with a “scale and complexity that begin to exceed that manageable by a human operator”, he says. For example, AI could be used to manage electricity shortfalls by briefly switching off power demand across entire communities or regions. “This might be thousands of refrigerators in people’s homes or large sites of demand, such as industrial plants,” he explains. “The speed and complexity of this task requires advanced AI.”

The speed and complexity of this task requires advanced AI.

Ceding control of your home to a remote AI might seem like the stuff of science fiction, but the integration of AI into our appliances is already underway. For example, AI is being used to manage energy use in a device most of us use every day – mobile phones. The latest iteration of Google’s Android phone operating system includes a function which studies your app habits to ensure battery is deployed only on the ones you like the most. Meanwhile, rarely used apps, which would previously hum away in the background consuming power, are shut down.

AI can now also work out how much electricity each of your home appliances is using, too. UK startup Verv uses AI to find the “fingerprint” of each appliance, using data from your electricity meter. Home appliance manufacturers will come under increasing pressure to produce energy-efficient products. With access to exactly what it costs to run a dishwasher or TV, consumers could rapidly become disenchanted with power-hungry devices. […]

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Der Beitrag How AI can help meet global energy demand erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.