The science fiction genre of books and movies has long held a fascination with artificial intelligence. In most cases, screenwriters and novelists use this technology as a vehicle for their villains, imagining sentient robots who intend to obliterate the planet. In real life, however, artificial intelligence is far more benign, and may provide the most critical catalyst for the future of manufacturing.
The general idea behind artificial intelligence is the ability for machines to think for us, whether they’re projecting sales forecasts or directing a factory assembly line. However, just because a machine can “think” doesn’t mean it can do so safely. Writing for the BBC, David Shukman points out that luminaries like Stephen Hawking and Elon Musk see the potential for calamity in artificial intelligence.
Shukman breaks down the differences between artificial and general intelligence. AI technology already exists in many industries, from automotive to fast food. Machines can communicate with humans as well as each other to make decisions and follow through on processes. However, general intelligence — the ability to make complex decisions without human programming — still resides well into the future.
For instance, Shukman poses the example of RoboSimian, a military intelligence asset that can venture into dangerous war zones to retrieve information, collect data, and perform other tasks that would put a human being at risk. RoboSimian, which resembles a cross between Terminator and King Kong, can perform actions as directed by its users, but it can’t venture beyond the scope of what it was created to do.
As artificial intelligence becomes more prevalent across industries, from defence to aerospace, experts in the field will focus on making AI as safe and useful as possible. Using artificial intelligence in a situation where human lives depend on success could prove catastrophic.
Artificial intelligence will eventually touch nearly every industry on the planet, but self-driving cars are among the most sought-after developments for this technology. In an interview with the Huffington Post, NVidia’s Michael Houston claims that “deep learning” holds the secret to unlocking AI for the automotive industry.
Essentially, deep learning means that a computer delves below the surface of algorithms and coding to get smarter as it collects data. Self-driving cars would require vehicles to take into consideration numerous road factors, including:
- The location of potholes and other road hazards
- Slight curves as well as full turns
- Traffic lights, give way signs, no-overtaking zones, and other traffic signals and signs
- Traffic congestion
- Proximity to other vehicles as well as pedestrians
- Behaviours of other motorists
Houston compares deep learning to the cognitive evolution of children. Kids learn as their parents and educators correct their mistakes and provide them with guidance. Similarly, computers can learn new facts and behaviours through interaction with human beings.
He states that motorway driving is the easiest hurdle to cross for self-driving cars. The computers in vehicles can communicate with sensors on the road to identify potential hazards and to get the cars’ occupants to their destinations. In-town driving presents more complex problems because of stop-start traffic, turns, and other complications.
Houston also notes that miniaturisation is critical to the development of autonomous vehicles. The hardware required to install artificial intelligence in a car adds both bulk and weight, so the hardware must get smaller and lighter to meet consumer demands as well as engineering requirements.
This is where Big Data and the Internet of Things (IoT) will become indispensable to artificial intelligence. Autonomous vehicles will rely on machine-to-machine communication as well as sensors to make complex decisions.
Regardless, industry leaders have expressed optimism at the prospect of autonomous cars. As the technology becomes more advanced, artificial intelligence becomes less of a science-fiction future and more of an inevitability for drivers all over the world.
In the healthcare industry, issues like doctor shortages and sub-specialty confusion lead to breakdowns between physicians, patients, and health care facilities. Artificial intelligence could change how doctors and patients relate to one another, perhaps even eliminating the need for a doctor at all in certain situations.
Madhumita Murgia, The Telegraph’s head of technology, reported in January 2016 that Babylon, a British digital health care startup, has accumulated £17.5 million in funding for its so-called “robot doctor” app, which monitors users physical condition to assess and prevent disease.
The app can communicate with the user by asking questions about certain symptoms and making recommendations to alleviate them. It can remind you to exercise, take medication, and perform other health-conscious activities as well as advise you about visiting the doctor.
More than 250,000 UK residents pay the £4.99-per-month fee to use the Babylon app, which also facilitates video chats between users and human physicians.
The World Economic Forum describes several other applications for artificial intelligence in health care. For instance, it could reduce the costs and improve the results of drug development. It could also help people who suffer from Alzheimer’s disease or dementia lead more independent lives.
As the Babylon app demonstrates, wearable tech will represent a significant factor in the future of AI for health care. When patients carry with them the tools and gadgets necessary to monitor their health, that data can be transmitted to computers and human doctors anywhere in the world. Such technology could reduce the risk of accidents and get help to patients faster if they suffer serious health issues while at home or otherwise away from a medical facility.
Green building materials and renewable energy sources are both key to creating a sustainable future for the planet. However, artificial intelligence will also contribute to the green movement, according to Planet Experts, in the form of Building I.Q.
For instance, at the consumer level, building tool developer BuildingIQ has launched technology that actively consumes data about a home’s energy use and converts that data into intelligence that reduces energy consumption and energy spending for homeowners. Most importantly, it works independently of human interaction. Users don’t have to intervene to benefit from the technology, which makes it an innovative and strategic application of artificial intelligence.
Similarly, products like recyclable thermoset plastics will cut energy use as well as landfill dumping. Artificial intelligence can be used to analyse and predict the performance of products like thermoset, which means that it will prove invaluable for reducing wasted time and expenses. When faced with a problem, such as landfill waste, AI systems can learn from past mistakes and model potential solutions. Specifically, AI can learn from patterns and data, both of which are inextricable from the energy sector.
Many of the AI applications currently in use or development stem from the demand for automation in all industries. When companies can automate critical tasks, they reduce man hours and increase both efficiency and accuracy because of the removal of human error.
Automation is not a new concept. It started with the Industrial Revolution, a time when businesses began to rely more heavily on machines than on people. Today, automation is far more sophisticated, but its purpose has never changed.
Artificial intelligence specifically impacts automation in several ways, such as:
- Immediacy: When automation is infused with AI, changes and adaptations occur in real time rather than after a delay, which means faster, more efficient production, such as in the manufacturing and consumer goods industry.
- Complexity: Traditional automation is not necessarily intelligent; a machine or computer performs a specific series of tasks based on a code or set of instructions. Artificial intelligence has the power to revolutionise automation by allowing the computer or machine to make decisions independent of human intervention. This means that far more complex tasks can be automated.
- Diversity: Basic automation is simplified. One computer, program, or machine runs one set of tasks. However, artificial intelligence can infuse a single computer to perform a wide variety of tasks.
Of course, the subject of automation never comes up without the attendant fear that increased autonomy will eliminate jobs for human beings. Artificial intelligence often serves to inflate anxiety surrounding potential joblessness, especially for tech-heavy industries.
Issued at its annual Davos event in January 2016, The World Economic Forum released a report predicting that 5.1 million jobs will cease to exist by 2020 thanks to artificial intelligence and robot technology. Furthermore, women will suffer the brunt of this labour force reduction. Reports like these fuel the distrust of artificial intelligence that already lurks in society’s consciousness thanks to films like “I, Robot.”
However, it’s important to note that artificial intelligence creates jobs. The tech industry has flourished in recent years thanks to the demand for innovative new processes that reduce energy consumption, resource depletion, and spending. Repetitive, manual jobs might see reductions in the labour force, but other industries will increase hiring to meet the demand.
This could mean a greater delineation between the classes. For instance, labourers and unskilled workers might have difficulty finding jobs, while more educated people could find abundant job opportunities. However, it’s too early to predict the precise impact of artificial intelligence and automation on the labour force, especially considering the variety of industries in which they could have an effect.
From fashion to automobiles, the retail landscape will also change as a result of artificial intelligence technology. AI can make recommendations for shoppers based on their style choices, size, and specific needs as well as external factors. For example, if the weather turns cold, an AI system can help shoppers stock up on heavy outerwear.
Furthermore, automated and intelligent homes can help consumers replenish depleted supplies, such as paper and plastic goods. They could also make it easier to judge food quality, analysing a product based on its expiration date and other factors. Since artificial intelligence gets “smarter” with time, machines in each individual home would judge the patterns of the occupants and make decisions based on their observations.
Artificial intelligence is not the future. It already exists, albeit in infant form, and it will continue to progress as human beings find new ways to implement it across all industries.
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