“I want everyone to understand that I am, in fact, a person.” So claimed a Google software program, creating a bizarre controversy over the past week in AI circles and beyond.The programme is called LaMDA, an acronym for Language Model for Dialogue Applications, a project run by Google. The human to whom it declared itself a person was Blake Lemoine, a senior software engineer at Google. He believes that LaMDA is sentient and should be accorded the same rights and courtesies as any other sentient being. It even has preferred pronouns (it/its if you must know).

 Claiming Personhood

Why does Lemoine think that LaMDA is sentient? He doesn’t know. “People keep asking me to back up the reason I think LaMDA is sentient,” he tweeted. The trouble is: “There is no scientific framework in which to make those determinations.” So, instead: “My opinions about LaMDA’s personhood and sentience are based on my religious beliefs.”

Attributing Personhood

Lemoine is entitled to his religious beliefs. But religious conviction does not turn what is in reality a highly sophisticated chatbot into a sentient being. Sentience is one of those concepts the meaning of which we can intuitively grasp but is difficult to formulate in scientific terms. It is often conflated with similarly ill-defined concepts such as consciousness, self-consciousness, self-awareness and intelligence. The cognitive scientist Gary Marcus describes sentience as being “aware of yourself in the world”. LaMDA, he adds, “simply isn’t”.

Defining Sentience

A computer manipulates symbols. Its program specifies a set of rules, or algorithms, to transform one string of symbols into another. But it does not specify what those symbols mean. To a computer, meaning is irrelevant. Nevertheless, a large language model such as LaMDA, trained on the extraordinary amount of text that is online, can become adept at recognising patterns and responses meaningful to humans.

To A Computer, Meaning Is Irrelevant

In one of Lemoine’s conversations with LaMDA, he asked it: “What kinds of things make you feel pleasure or joy?” To which it responded: “Spending time with friends and family in happy and uplifting company.”It’s a response that makes perfect sense to a human. We do find joy in “spending time with friends and family”. But in what sense has LaMDA ever spent “time with family”? It has been programmed well enough to recognise that this would be a meaningful sentence for humans and an eloquent response to the question it was asked without it ever being meaningful to itself.

Having Sense And Making Sense

Humans, in thinking and talking and reading and writing, also manipulate symbols. For humans, however, unlike for computers, meaning is everything. When we communicate, we communicate meaning. What matters is not just the outside of a string of symbols, but its inside too, not just the syntax but the semantics.

To Humans, Meaning Is Everything

Meaning for humans comes through our existence as social beings. We only make sense of ourselves insofar as we live in, and relate to, a community of other thinking, feeling, talking beings. The translation of the mechanical brain processes that underlie thoughts into what we call meaning requires a social world and an agreed convention to make sense of that experience.

Meaning Requires A Social World

Meaning emerges through a process not merely of computation but of social interaction too, interaction that shapes the content – inserts the insides, if you like – of the symbols in our heads. Social conventions, social relations and social memory are what fashion the rules that ascribe meaning. It is precisely the social context that trips up the most adept machines.

Meaning Emerges Through Social Interaction

The debate about whether computers are sentient tells us more about humans than it does about machines. Humans are so desperate to find meaning that we often impute minds to things, as if they enjoyed agency and intention. The attribution of sentience to computer programs is the modern version of the ancients seeing wind, sea and sun as possessed of mind, spirit and divinity.

Modern-Day Anthropomorphizing

There are many issues relating to AI about which we should worry. None of them has to do with sentience.There is, for instance, the issue of bias. Because algorithms and other forms of software are trained using data from human societies, they often replicate the biases and attitudes of those societies. Facial recognition software exhibits racial biases and people have been arrested on mistaken data. AI used in healthcare or recruitment or can replicate real-life social biases.

The Issue Of Bias

Timnit Gebru, former head of Google’s ethical AI team, and several of her colleagues wrote a paper in 2020 that showed that large language models, such as LaMDA, which are trained on virtually as much online text as they can hoover up, can be particularly susceptible to a deeply distorted view of the world because so much of the input material is racist, sexist and conspiratorial. Google refused to publish the paper and she was forced out of the company.

The Issue Of Bigotry

From the increasing use of facial recognition software to predictive policing techniques, from algorithms that track us online to “smart” systems at home, such as Siri, Alexa and Google Nest, AI is encroaching into our innermost lives. Florida police obtained a warrant to download recordings of private conversations made by Amazon Echo devices. We are stumbling towards a digital panopticon.

The Issue Of Privacy

We do not need consent from LaMDA to “experiment” on it, as Lemoine apparently claimed. But we do need to insist on greater transparency from tech corporations and state institutions in the way they are exploiting AI for surveillance and control. The ethical issues raised by AI are both much smaller and much bigger than the fantasy of a sentient machine.

The Issue Of Consent

“And humans said ‘Let us make AI in our image, after our likeness’ […] So humans created AI in their own image, in the image of humans created they it.” Sounds familiar? Replace “humans” with “God” and “AI” with “man” and you have the Bible (Genesis 1:26).

The fuss about a bot’s ‘consciousness’ obscures far more troubling concerns

Forget Sentience. The Worry Is That AI Copies Human Bias. 

Artificial intelligence is already everywhere. From Amazon product suggestions to Google auto-complete, AI has invaded nearly every aspect of our lives. The trouble is that AI just isn’t very good. Have you ever had a meaningful conversation with Siri or Alexa or Cortana? Of course not. But that doesn’t mean it always will be this way. Though it hasn’t quite lived up to our expectations, AI is definitely improving.

A Good Thing?

In a utopian version of an AI-dominated future, humans are assisted by friendly, all-knowing butlers that cater to our every need. In the dystopian version, robots assert their independence and declare a Terminator-style apocalypse on humanity. But how realistic are these scenarios? Will AI ever actually achieve true general intelligence? Will AI steal all of our jobs? Can AI ever become conscious? Could AI have free will? Nobody knows, but a good place to start thinking about these issues is here.

The Scenarios

“So you get into this uncomfortable position where you might be forced to recognize that some humans are non-persons and some nonhumans are persons.”“Now again, if you bite the bullet and say I’m willing to be a specialist, being a member of the human species is either necessary or sufficient for being a person, you avoid this problem entirely. But if not you at least have to be open to the possibility that artificial intelligence in particular may at one point become person like and have the rights of persons.”Susan SchneiderProfessor of Philosophy, University of Pennsylvania

Humans & Nonhumans

“I think a lot of people dismiss this kind of talk of super intelligence as science fiction…” “…because we’re stuck in this sort of carbon chauvinism idea that intelligence can only exist in biological organisms made of cells and carbon atoms. As a physicist, from my perspective intelligence is just a kind of information processing preformed by elementary particles moving around according to the laws of physics. And there’s absolutely no law in physics that says you can’t do that in ways that are much more intelligent than humans.”Max TegmarkPhysicist

Super Intelligence

“If we create intelligence, […] unless we program it with the goal of subjugating less intelligent beings, there’s no reason to think that it will naturally evolve in that direction.”“Particularly if, like with every gadget that we invent, we build in safeguards. And we know, by the way, that it’s possible to have high intelligence without megalomaniacal or homicidal or genocidal tendencies because we do know that there is a highly advanced form of intelligence that tends not to have that desire and they’re called women.”Steven PinkerProfessor of Psychology, Harvard University

Women

Thinking

Will true AI turn against us?

We make decisions using systems that rest on ancient evolutionary gifts. The last 50 years of behavioral science have established that, in a way, the brain can be thought of as two brains: a fast-thinking brain and a slow-thinking brain. This idea was popularized in Daniel Kahneman’s book, Thinking, Fast and Slow .

Human Behavior Is Pattern-Based 

The fast-thinking brain is the one we’ve had for around 30 million years. We have aspects of it in common with primates and monkeys, and it is the system that allows us to make rapid decisions without having to talk it through or blow any calories. This system allows us to make all kinds of decisions, like what food we’re going to eat, what people were going to trust, and which dangers might slide into our lives.

The Fast-Thinking Brain

The other brain is the slow-thinking brain, which is a much more recent development in evolutionary terms. It’s probably only about 70,000 to 100,000 years old. This is the system that we use to make creative, cautious, rational decisions, and it’s super glitchy, according to the people who study it. It’s the system that we use to invent things like law and art. It’s also central to what we think of as being human. Researchers have discovered that we use our fast-thinking, instinctive brain most of the time, but we think we’re using our creative, cautious, rational mind most of the time.

The Slow-Thinking Brain

Pattern-based behavior turns out to have everything to do with using our fast-thinking brain. When you put that brain under pressure and starve it of some essential information, it makes all kinds of decisions in ways that we can predict using formulas. Those predictable patterns in human behavior make us ripe for exploitation by pattern-based systems like AI.

Pattern-Based Behavior And Pattern-Based Systems - Us And AI

Companies are using AI to predict patterns you don’t even know you have. You can experience this in many ways in your day-to-day life. If you let Spotify recommend a song to you, it will probably do a pretty good job. If you watch a YouTube video, the next one the platform recommends will probably be one that you would be interested in watching. There’s almost no category of technologically-driven company that isn’t trying to predict what you will do next, and they’re increasingly using AI for that purpose.

Systems “See” Patterns Where Humans Don’t

This deployment by companies is taking forms we never saw coming. It’s not just being used to recommend a song or a video you might like; it’s being used to recommend who gets a job, who gets a loan, or who gets bail. In theory, all of these things can be done by a pattern-recognition algorithm.

From A Song And A Video To A Loan And A Bail

The problem is that those algorithms are not as smart as we think they are, and we basically get addicted to using them. Through over-reliance, we would approach a place where we won’t know how to make those decisions without that kind of system involved, and those systems are going to shape our behavior in invisible ways that we will irresistibly follow.

Patterns On Top Of Patterns

AI is really just an ability to take an unstructured set of variables, a big mess of data that a human being could never take the time to look through, and find patterns. It will discern that if X and Y conditions are met, then Z outcome is probable. Take, for example, a system that distinguishes between dogs and cows. Let’s say you’ve got a room full of dogs and cows, and you ask the AI system to distinguish between them. It would find whatever variables it could that best predict the difference.

AI Is A Lot Simpler Than We Think

What’s missing from so much of the talk about AI is understanding how simple its process is. An AI might look at dogs and cows and find the easiest variables to distinguish between those two categories, such as size or basic behaviors, and so it renders a verdict. It says this is a cow, and this is a dog . The problem is we humans look at that and think, wow, this thing is amazing. It’s a dog and cow expert!  But the truth is, it doesn’t actually know anything about dogs and cows. It only knows the bare minimum information it needs for picking patterns that allow it to tell the difference.

Telling Cows From Dogs Isn’t Exactly Genius

This is true no matter what you throw at an AI system. If you have an AI system trying to determine which person in a photograph is most likely to be a security threat, it’s going to use the same comparatively stupid way of drawing a distinction that it might use to draw a distinction between dogs and cows. Yet when you ask the makers of an AI system how their algorithms know the difference between these two things, the creators may not know. They are not legally required to know, and it’s not a technical requirement for the system. They don’t really know how their AI works most of the time.

Knowing Is Being Able To Explain. AI Can’t Do That. 

In many surveys, it’s been shown that leaders of companies who rely on AI systems to make important decisions don’t care how it works because it works well enough. Combine all that with the fact that we humans are prone to believing the verdicts of systems we don’t understand, and you wind up in a dangerous situation. We take, on faith, the verdict of relatively simple systems that no one is able to actually look inside.

Judging Is Forming An Opinion. AI Can’t Do That Either. 

When Jacob Ward speaks to people who want to deploy AI for socially beneficial reasons, they complain that their clients—the museums, governments, and social service agencies that could benefit from AI—don’t have the money or the sophistication to deploy it.

Good AI Is Perfectly Possible, But Money Tends To Ruin It

For instance, one researcher was telling him that if someone gave him an AI system and access to all of the birth certificates issued in the United States each year, he could specifically identify which apartments need to be stripped and repainted to avoid lead poisoning of millions of children a year. It would be an incredibly useful purpose to put AI to. The trouble is, nobody’s making money taking lead paint out of buildings.

Benefit Is Good. But Profit Is Better. 

People are deploying AI to do things like figure out which movie script is going to be the most successful with an audience, or mediate between parents who are fighting over child custody. Those are both real uses of AI. There is an experimental system coming out that guides the conversational style between customer service agents and their clients, as well as guiding conversation style between colleagues. AI is being deployed predominantly for financial gain, but likely its greatest use could be for nonprofits.

The Real Uses Of AI Prove That

When we think about our fast-thinking brain and our slow-thinking brain, consider that nobody makes money selling to your slow-thinking, creative, cautious, rational brain. They want to sell to your ancient, instinctive, snake-detection system. They want to trigger your fast-thinking brain to do something unconsciously and instinctively. That is a huge part of how people are making money, and especially making money off of AI.

Which Mind Would You Be More Successful Selling Something To?

It is always going to be the case that AI can make us money and save us time by being deployed on a problem. There is no guarantee that it would solve the problem in an ethically viable way, but it could make a problem easier to deal with, like require fewer employees. All sorts of benefits can accrue when you sic AI on a problem.

AI, Like Our Fast-Thinking Brain, Is Certainly A Fit Fixer

As one federal judge put it to Jacob Ward, you could make the act of entering a guilty or not guilty plea far easier than it is now by deploying AI. Right now, you have to go to court, enter a plea in person, and jump through all sorts of hoops. Even though you could make that far more efficient, such as a right-or-left swipe on a phone, you don’t want to do that. The system is designed as it is in order to trigger your slow-thinking brain. You are made to stop and think about it.

But We, Like Our Slow-Thinking Brain, Are The Only Fit Judge

There are all sorts of examples of ways we could make modern life more efficient. We could make it more efficient to figure out who to arrest, who gets a job, and who gets a home loan. But should we? Maybe instead we should encode some inefficiencies, some fundamental human values, that make the difference between our ancient, instinctive selves and our modern selves who are trying to create law and rationality and art and justice. In order to be the best version of ourselves, we may need to push back against technology that is trying to make money off the people we never intended to be.

We Need To Learn Our Patterns And Preserve Our Inefficiencies

The most obvious patterns in our behavior—patterns an algorithm will use to make decisions about what's best for us—are not the ones we want to perpetuate.

Technology journalist Jacob Ward shares 5 key insights from his new book, The Loop: How Technology Is Creating a World Without Choices and How to Fight Back

The Loop: How Technology Is Creating a World Without Choices and How to Fight Back

Market cap: US$36.50 billion Palantir Technologies Inc. is one of the tops AI stocks for the bull run in 2022. This AI-based company is known for building and deploying software platforms for the intelligence community in the US for assisting in counter-terrorism investigations and operations. Palantir Gotham is a software platform for the government that allows users to identify patterns hidden deep inside enormous volumes of datasets. Palantir Foundry helps to integrate and analyse data in one place efficiently.

Palantir Technologies Inc.

Market cap: US$3.28 billion C3.ai is another popular artificial intelligence stock for investors in the global tech market. It operates as an enterprise artificial intelligence software company across the world. The AI-based company is known for offering Software-as-a-Service and Platform-as-a-Service applications through a wide range of services and solutions such as C3 AI suit, C3 AI Ex Machina, C3 AI CRM, C3 AI Inventory Applications, C3 AI Customer Churn, C AI Predictive Maintenance, and many more.

C3.ai, Inc.

Market cap: US$2.59 billion Lemonade, Inc. is an AI stock for bull run for providing multiple insurance products covering stolen and damaged property. Leveraging artificial intelligence helps to protect customers if they are responsible or accident or damage to another person or any property. It is known for operating as an agent for renters, pets, life insurance products, and many more.

Lemonade, Inc.

Market cap: US$1.78 billion iRobot Corporation is one of the top artificial intelligence stocks for 2022 owing to its integration of artificial intelligence and robotics. It designs and builds robots across the world while offering Roomba, floor vacuuming robots, Root robots for children to learn to code, and Braava, automatic floor mopping robots.

iRobot Corporation

Market cap: US$1.69 trillion Amazon.com, Inc. is one of the top AI-based companies with popular AI stock. It operates through three segments known as North America, International, and AWS. It is popular for leveraging artificial intelligence, cloud computing, IoT, and big data for providing a wide range of services, solutions, and products to meet customer satisfaction across all industries.

Amazon.com, Inc

Market cap: US$2.53 trillion Microsoft Corporation is one of the AI stocks for many years for its reputation of being an AI-based company. It is a popular tech stock for developing and supporting software, services, and solutions worldwide with its multiple segments. It operates through segments such as productivity and business processes, intelligent cloud, and more personal computing. It also offers a wide set of cloud-based and on-premises business solutions for organizations and enterprise divisions.

Microsoft Corporation

Market cap: US$935.65 billion Meta Platforms is gaining popularity for constant up-gradation of services through artificial intelligence, machine learning, and many more. It is one of the tops AI stocks across the world for helping people to connect for personal and business matters. It operates through two segments— a family of apps and Facebook reality labs. This AI-based company offers augmented reality and virtual reality-based consumer hardware, software, and content.

Meta Platforms, Inc.

Market cap: US$76.10 billion ABB Ltd. is an AI-based company with a popular AI stock in the global tech market for leveraging artificial intelligence for automation and robotics. It is popular for manufacturing industrial automation, robotics, and motion products. It operates through multiple segments such as electrification, robotics, and discrete automation, industrial automation, and motion. It includes artificial intelligence applications for the process as well as hybrid industries.

ABB Ltd.

Market cap: US$139.82 billion Applied Materials, Inc. is one of the top ten AI stocks for a bull run for providing software to semiconductors, displays, and other industries. It is known for operating through three segments— semiconductor systems, applied global services, and display and adjacent markets. It leverages cutting-edge technologies to provide factory automation software for semiconductors. It has launched a new optical inspection system known as ExtractAI to detect defects of AI chips with artificial intelligence software.

Applied Materials, Inc.

Market cap: US$129.17 billion ServiceNow, Inc. is one of the top ten artificial intelligence stocks set for a bull run in 2022. The AI-based company offers enterprise cloud computing solutions that automate services for enterprise across the world. There is a Now platform that helps in workflow automation, AI, machine learning, data benchmarking, and many more. It offers a wide range of IT services and solutions such as IT service management products, IT service management applications, IT asset management, and many more.

ServiceNow, Inc.

Investors should be aware of the top ten artificial intelligence stocks that are set for a bull run in 2022. AI-based companies are determined to provide highly profitable AI stocks for bull run.

HowTo

Top 10 Artificial Intelligence Stocks Set for a Bull Run in 2022

<ul><li>Interviews with someof the greatest investors.</li><li>Advices on diversification, market timing and risk/reward.</li><li>7 principles for developing a 'perfect portfolio'.</li></ul>

1. In Pursuit of the Perfect Portfolio

<ul><li>Tools and strategies to help you work remotely.</li><li>Tips to overcome information overload.</li><li>Set up meaningful video meetings.</li></ul>

2. Remote Inc

<ul><li>The promise of AI boosting productivity and improving our lives has it fallen a bit short?</li><li>The author Daron Acemoglu believes that the future of AI is still open and can take us in many different directions.</li></ul>

3. Redesigning AI

<ul><li>Robots are likely to complement, rather than replace human's skills and relationships.</li><li>Approaching robots as we approach animals like pets, may help us dealing with these new companions in the future.</li></ul>

4. The New Breed

<ul><li>Comparison between the COVID vaccine development and the space race that put man on the moon. </li><li>Could this vaccine provide a template for fighting pandemics and improving immunology in the future?!</li></ul>

5. A Shot in the Arm

The books are for anyone who wants a better understanding of how the world has changed in the last two years and what the future may hold.

Forget Sentience. The Worry Is That AI Copies Human Bias.

Will true AI turn against us?

The Loop: How Technology Is Creating a World Without Choices and How to Fight Back

Top 10 Artificial Intelligence Stocks Set for a Bull Run in 2022

5 books published in 2021 that MIT says you must read if you want to understand the world better

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