In today’s global manufacturing sector, there are a few main ways in which AI is deployed along with robotics. AI is a highly useful tool in robotic assembly applications. When combined with advanced vision systems, AI can help with real-time course correction, which is particularly useful in complex manufacturing sectors like aerospace. AI can also be used to help a robot learn on its own which paths are best for certain processes while it’s in operation.

Robots are machines or mechanical human beings that are designed to assist humans with laborious and complex tasks. However, such robots are no more just mechanical design rather they have become smarter with time and advancement of technologies. AI developments have induced evolution and better capacity in robots. Even robotics and AI together can revolutionize almost any industry for the greater good.

Using AI’s subset Machine Learning (ML), if we design a system where the device learns from its mistakes and automatically compensates for errors as it works, then we’ve successfully combined AI and robotics. The combination of these technologies has the potential to make people’s lives a lot easier. People can monitor the performance of robots as opposed to manually performing tasks themselves. The downside of these systems would be that the labour demand for any industry that utilizes these robots will be far less. The robots will correct themselves if any errors arise, and only massive, glaring problems would need a human to address them.

Well, some of them have already arrived in the market. In CES 2020, Samsung unveiled a bot chef who is capable of making people a salad on their command. Also, Delta Airlines showcased an exoskeleton that can boost the strength and endurance of the human body. We can observe that robotics offers a lot of promise from the creation of artificial limbs to entire suits that can help people performs difficult tasks so much easier. Amid this, the amalgamation of AI and robotics introduces interesting interplays. The industry can be benefitted from earnest promises of AI + Robots.

While businesses through increased demand to drive down prices will eventually make these machines affordable, for the time being (and for quite a while into the future), the application of AI and robotics as a combined unit remains too expensive to apply to routine tasks. As development in the field moves forward, we may see robots that work on machine learning within the next decade. The question of whether humanity is ready for the impact it will make both socially and economically is something that experts are still debating today.

Moreover, robotics packaging uses forms of AI frequently for quicker, lower cost and more accurate packaging. AI helps save certain motions a robotic system makes, while constantly refining them, which makes installing and moving robotic systems easy enough for anybody to do.

Furthermore, robots are now being used in a customer service capacity in retail stores and hotels around the world. Most of these robots leverage AI’s natural language processing abilities to interact with customers in a more human way. Often, the more these systems can interact with humans, the more they learn.

A handful of robotic systems are now being sold as open-source systems with AI capability. This way, users can teach their robots to do custom tasks based on their specific applications, such as small-scale agriculture. The convergence of open source robotics and AI could be a huge trend in the future of AI robots.

When working together, robots are smarter, more accurate and more profitable. AI has yet to come close to reaching its full potential, but as it advances, so will robotics.

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“Success in creating effective AI could be the biggest event in the history of our civilisation. Or the worst. We just don’t know,” said Professor Stephen Hawking at this week’s Web Summit in Lisbon.

Along with many benefits, said Hawking, artificial intelligence (AI) brings many “dangers, like powerful autonomous weapons, or new ways for the few to oppress the many”.

The physicist called for new regulation to ensure humanity could prevent AI from threatening its existence. 

“Perhaps we should all stop for a moment and focus not only on making our AI better and more successful, but also on the benefit of humanity,” he added.

Hawking is not the only luminary from the science and technology world to have warned about the future of AI.

We should all “be very careful about artificial intelligence”, Bill Gates said earlier this year. “If I had to guess at what our biggest existential threat is, it’s probably that. With artificial intelligence, we’re summoning the demon.”

In recent months, there have been headlines about killer robots and about automation replacing human workers, but also about algorithms that help diagnose cancer, and the successful development of self-driving cars.

“Some scholars argue it is the most pressing existential risk humanity might ever face, while others mostly dismiss the hypothesised danger as unfounded doom-mongering,” says Motherboard’s Phil Torres.

So should we be worried about the spread of AI? And what we can do about it?

The reaction to AI

A YouGov survey last year of more than 2,000 people found that public attitudes towards AI vary greatly depending on its application.

Some 70% of respondents were happy for intelligent machines to carry out seemingly menial jobs such as crop monitoring – but this fell to 49% when it came to household tasks, while only 23% would be happy for robots to perform medical operations. And a mere 17% were comfortable with the idea of so-called sex robots.

One of the primary worries about AI is its impersonal nature.

In August, Tesla and SpaceX CEO Elon Musk, along with 115 other AI and robotics specialists, signed an open letter urging the UN to recognise the dangers of lethal autonomous weapons and to ban their use internationally.

According to the Human Rights Watch organisation, the US, China, Israel, South Korea, Russia and the UK “have been investing in developing weapons systems with decreasing levels of human control in the critical functions of selecting and engaging targets”.

Steven Finlay, author of Artificial Intelligence and Machine Learning for Business, believes that autonomous armed robots that can track and target people, using facial recognition software, are just around the corner.

AI and robotics are advancing so quickly that within years, wars could be fought with autonomous weapons and vehicles, reports The Guardian.

Regulate or exterminate?

AI regulation is one answer to the problem.

“A healthy modern democracy requires ordinary citizens to participate in public discussions about rapidly advancing technologies. We desperately need new policies, regulations, and safety nets for those displaced by machines,” says The Nation’s Katharine Dempsey.

Elon Musk agrees. Back in 2014, he said: “I’m increasingly inclined to think that there should be some regulatory oversight, maybe at the national and international level, just to make sure that we don’t do something very foolish.”

Arguably, the greatest worry is that machines may become better at making decisions than humans, enslaving humanity to automated decision-makers and whoever controls them.

AI-based systems are already replacing many jobs. For example, some AI machines can spot skin cancer as accurately as a human doctor, Wired reports.

Many of our choices are already influenced by AI, via websites such as Amazon and Facebook. Algorithms determine the content we see online, and make recommendations about everything from what we watch on TV and where we eat to who we date.

“What makes this scenario so dangerous is that it isn’t being planned by some overarching master intelligence or machine overlord,” says Steven Finlay. “We are creating the very technology that could lead to our demise.”

A change for the better?

It’s not all doom and gloom.

“I’m optimistic that we can create an inspiring future with AI if we win the race between the growing power of AI and the growing wisdom with which we manage it, but that’s going to require planning and work,” physicist Max Tegmark, author of Life 3.0: Being Human in the Age of Artificial Intelligence, told Motherboard.

While Tegmark advocates regulation, he argues that there also needs to be a focus on the upside to using AI. “If people just focus on the downsides, they get paralysed by fear and society gets polarised and fractured,” he concludes.

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Some people are afraid that heavily armed artificially intelligent robotsmight take over the world, enslaving humanity – or perhaps exterminating us. These people, including tech-industry billionaire Elon Musk and eminent physicist Stephen Hawking, say artificial intelligence technology needs to be regulated to manage the risks. But Microsoft founder Bill Gates and Facebook’s Mark Zuckerberg disagree, saying the technology is not nearly advanced enough for those worries to be realistic.

As someone who researches how AI works in robotic decision-making, drones and self-driving vehicles, I’ve seen how beneficial it can be. I’ve developed AI software that lets robots working in teams make individual decisions, as part of collective efforts to explore and solve problems. Researchers are already subject to existing rules, regulations and laws designed to protect public safety. Imposing further limitations risks reducing the potential for innovation with AI systems.

How is AI regulated now?

While the term “artificial intelligence” may conjure fantastical images of human-like robots, most people have encountered AI before. It helps us find similar products while shopping, offers movie and TV recommendations and helps us search for websites. It grades student writing, provides personalized tutoring and even recognizes objectscarried through airport scanners.

In each case, the AI makes things easier for humans. For example, the AI software I developed could be used to plan and execute a search of a field for a plant or animal as part of a science experiment. But even as the AI frees people from doing this work, it is still basing its actions on human decisions and goals about where to search and what to look for.

In areas like these and many others, AI has the potential to do far more good than harm – if used properly. But I don’t believe additional regulations are currently needed. There are already laws on the books of nations, states and towns governing civil and criminal liabilities for harmful actions. Our drones, for example, must obey FAA regulations, while the self-driving car AI must obey regular traffic laws to operate on public roadways.

Existing laws also cover what happens if a robot injures or kills a person, even if the injury is accidental and the robot’s programmer or operator isn’t criminally responsible. While lawmakers and regulators may need to refine responsibility for AI systems’ actions as technology advances, creating regulations beyond those that already exist could prohibit or slow the development of capabilities that would be overwhelmingly beneficial.

Potential risks from artificial intelligence

It may seem reasonable to worry about researchers developing very advanced artificial intelligence systems that can operate entirely outside human control. A common thought experiment deals with a self-driving car forced to make a decision about whether to run over a child who just stepped into the road or veer off into a guardrail, injuring the car’s occupants and perhaps even those in another vehicle.

Musk and Hawking, among others, worry that hypercapable AI systems, no longer limited to a single set of tasks like controlling a self-driving car, might decide it doesn’t need humans anymore. It might even look at human stewardship of the planet, the interpersonal conflicts, theft, fraud and frequent wars, and decide that the world would be better without people.

Science fiction author Isaac Asimov tried to address this potential by proposing three laws limiting robot decision-making: Robots cannot injure humans or allow them “to come to harm.” They must also obey humans – unless this would harm humans – and protect themselves, as long as this doesn’t harm humans or ignore an order.

But Asimov himself knew the three laws were not enough. And they don’t reflect the complexity of human values. What constitutes “harm” is an example: Should a robot protect humanity from suffering related to overpopulation, or should it protect individuals’ freedoms to make personal reproductive decisions?

We humans have already wrestled with these questions in our own, nonartificial intelligences. Researchers have proposed restrictions on human freedoms, including reducing reproduction, to control people’s behavior, population growth and environmental damage. In general, society has decided against using those methods, even if their goals seem reasonable. Similarly, rather than regulating what AI systems can and can’t do, in my view it would be better to teach them human ethics and values – like parents do with human children.

Artificial intelligence benefits

People already benefit from AI every day – but this is just the beginning. AI-controlled robots could assist law enforcement in responding to human gunmen. Current police efforts must focus on preventing officers from being injured, but robots could step into harm’s way, potentially changing the outcomes of cases like the recent shooting of an armed college student at Georgia Tech and an unarmed high school student in Austin.

Intelligent robots can help humans in other ways, too. They can perform repetitive tasks, like processing sensor data, where human boredom may cause mistakes. They can limit human exposure to dangerous materials and dangerous situations, such as when decontaminating a nuclear reactor, working in areas humans can’t go. In general, AI robots can provide humans with more time to pursue whatever they define as happiness by freeing them from having to do other work.

Achieving most of these benefits will require a lot more research and development. Regulations that make it more expensive to develop AIs or prevent certain uses may delay or forestall those efforts. This is particularly true for small businesses and individuals – key drivers of new technologies – who are not as well equipped to deal with regulation compliance as larger companies. In fact, the biggest beneficiary of AI regulation may be large companies that are used to dealing with it, because startups will have a harder time competing in a regulated environment.

The need for innovation

Humanity faced a similar set of issues in the early days of the internet. But the United States actively avoided regulating the internet to avoid stunting its early growth. Musk’s PayPal and numerous other businesses helped build the modern online world while subject only to regular human-scale rules, like those preventing theft and fraud.

Artificial intelligence systems have the potential to change how humans do just about everything. Scientists, engineers, programmers and entrepreneurs need time to develop the technologies – and deliver their benefits. Their work should be free from concern that some AIs might be banned, and from the delays and costs associated with new AI-specific regulations.

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Robotic artificial intelligence platforms that are increasingly replacing human decision makers are inherently racist and sexist, experts have warned.

Programmes designed to “pre-select” candidates for university places or to assess eligibility for insurance cover or bank loans are likely to discriminate against women and non-white applicants, according to recent research.

Professor Noel Sharkey, Co-Director of the Foundation for Responsible Robotics, said more women need to be encouraged into the IT industry to redress the automatic bias.

He said the deep learning algorithms which drive AI software are “not transparent”, making it difficult to to redress the problem.

Currently approximately 9 per cent of the engineering workforce in the UK is female, with women making up only 20 per cent of those taking A Level physics.

“We have a problem,” Professor Sharkey told Today.

“We need many more women coming into this field to solve it.”

His warning came as it was revealed a prototype programme developed to short-list candidates for a UK medical school had negatively selected against women and black and other ethnic minority candidates.

Professor Sharkey said researchers at Boston University had demonstrated the inherent bias in AI algorithms by training a machine to analyse text collected from Google News.

When they asked the machine to complete the sentence “Man is to computer programmers as woman is to x”, the machine answered “homemaker”.

A separate US built a platform intended to accurately describe pictures, having first examined huge quantities of images from social media.

It was shown a picture of a man in the kitchen, yet still labelled as a woman in the kitchen.

Maxine Mackintosh, a leading expert in health data, said the problem is mainly the fault of skewed data being used by robotic platforms.

“These big data are really a social mirror – they reflect the biases and inequalities we have in society,” she told the BBC.

“If you want to take steps towards changing that you can’t just use historical information.”

In May last year report claimed that a computer program used by a US court for risk assessment was biased against black prisoners.

The Correctional Offender Management Profiling for Alternative Sanctions, was much more prone to mistakenly label black defendants as likely to reoffend according to an investigation by ProPublica.

The warning came as in the week the Ministry of Defence said the UK would not support a change of international law to place a ban on pre-emptive “killer robots”, able to identify, target and kill without human control.

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LONDON — Artificial intelligence robots are turbocharging the race to find new drugs for the crippling nerve disorder ALS, commonly called Lou Gehrig’s disease.

The condition attacks and kills nerve cells controlling muscles, leading to weakness, paralysis and, ultimately, respiratory failure.

There are only two drugs approved by the U.S. Food and Drug Administration to slow the progression of ALS (amyotrophic lateral sclerosis), one available since 1995 and the other approved just this year. About 140,000 new cases are diagnosed a year globally, and there is no cure.

“Many doctors call it the worst disease in medicine, and the unmet need is huge,” said Richard Mead of the Sheffield Institute of Translational Neuroscience, who has found artificial intelligence (AI) is already speeding up his work.

Such robots — complex software run through powerful computers — work as tireless and unbiased super-researchers.

They analyze huge chemical, biological and medical databases, alongside reams of scientific papers, far quicker than humanly possible, throwing up new biological targets and potential drugs.

Cell deaths prevented

One candidate proposed by AI machines recently produced promising results in preventing the death of motor neurone cells and delaying disease onset in preclinical tests in Sheffield.

Mead, who aims to present the work at a medical meeting in December, is now assessing plans for clinical trials.

He and his team in northern England are not the only ones waking up to the ability of AI to elucidate the complexities of ALS.

In Arizona, the Barrow Neurological Institute last December found five new genes linked to ALS by using IBM’s Watson supercomputer. Without the machine, researchers estimate the discovery would have taken years rather than only a few months.

Mead believes ALS is ripe for AI and machine-learning because of the rapid expansion in genetic information about the condition and the fact there are good test-tube and animal models with which to evaluate drug candidates.

That is good news for ALS patients seeking better treatment options. Famous sufferers include Gehrig, the 1923-39 New York Yankees baseball player; actor and playwright Sam Shepard, who died last month; and cosmologist Stephen Hawking, a rare example of someone living for decades with the condition.

If the research goes on to deliver new medicines, it would mark a notable victory for AI in drug discovery, bolstering the prospects of a growing batch of startup companies focused on the technology.

Those firms are based on the premise that while AI robots won’t replace scientists and clinicians, they should save time and money by finding drug leads several times faster than conventional processes.

British ‘unicorn’

Mead from Sheffield is working with BenevolentAI, one of a handful of British “unicorns” — private companies with a market value above $1 billion, in this case $1.7 billion — which is rapidly expanding operations at its offices in central London.

Others in the field include Scotland’s Exscientia and U.S.-based firms Berg, Numerate, twoXAR, Atomwise and InSilico Medicine — the last of which recently launched a drug discovery platform geared specifically to ALS.

A view of BenevolentAI’s home page.

“What we are trying to do is find relationships that will give us new targets in disease,” said Jackie Hunter, a former drug hunter at GlaxoSmithKline (GSK) who now heads Benevolent’s pharma business. “We can do things so much more dynamically and be really responsive to what essentially the information is telling us.”

Unlike humans, who may have pet theories, AI scans through data and generates hypotheses in an unbiased way.

Conventional drug discovery remains a hit-and-miss affair, and Hunter believes the 50 percent failure rates seen for experimental compounds in mid- and late-stage clinical trials due to lack of efficacy is unsustainable, forcing a shift to AI.

A key test will come with a study by Benevolent to assess a previously unsuccessful compound from Johnson & Johnson in a new disease area — this time for treating Parkinson’s disease patients with excessive daytime sleepiness.

Big pharmaceutical companies like GSK, Sanofi and Merck are now exploring the potential of AI through deals with startups.

Being careful

They are treading cautiously, given the failure of “high throughput screening” in the early 2000s to improve efficiency by using robots to test millions of compounds. Yet AI’s ability to learn on the job means things may be different this time.

CPR Asset Management fund manager Vafa Ahmadi, for one, believes it is a potential game-changer.

“Using artificial intelligence is going to really accelerate the way we produce much better targeted molecules. It could have a dramatic impact on productivity, which in turn could have a major impact on the valuation of pharmaceutical stocks,” he said.

Drugmakers and startups are not the only ones chasing that value. Technology giants including Microsoft, IBM and Google’s parent Alphabet are also setting up life sciences units to explore drug R&D.

For Benevolent’s Hunter, today’s attempts to find new drugs for ALS and other difficult diseases amount to an important test vehicle for the future of AI, which is already being deployed in other high-tech areas such as autonomous cars.

“The aim is to show that we can deliver in a very difficult and complex area, ” Hunter said. “I believe if you can do it in drug discovery and development, you can show the power of AI anywhere.”

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