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How do we know when artificial intelligence has become sentient?


Artificial intelligence research has accelerated in recent years and people are interacting with AI more frequently. In-home AI assistants and self-driving cars Once things were out of science fiction but now they are becoming reality.

Some researchers and activists wonder if AI is nearing the point of sentience, the ability to think and feel at the same level as humans. Some worry that sentient AI could overtake humanity, while others worry about subjugating intelligent life forms to do our bidding.

So, how do we know if AI has become sentient? We’ll break down the history of AI, where AI research is now, and how, or even if, we can determine if AI has crossed the border into emotion.

Key takeaways

  • Artificial intelligence research began in the mid-1950s with the search for artificial general intelligence.
  • Today, much of AI research focuses on specific tasks rather than general intelligence
  • Given our current understanding of consciousness, it is impossible to determine whether AI is sentient.

A Brief History of Artificial Intelligence

Artificial intelligence has a long history, with early formulations in stories told thousands of years ago. Greek mythology speaks of Telos, a giant bronze statue that guards the island of Crete and circles the island’s shores three times a day. Although the Greeks obviously wouldn’t have described telos using the language we use to describe AI today, it’s interesting how long humans have thought about the line between man and machine.

However, only recently has AI become something that humans can study and develop. Many experts point to 1956 as the year when AI research officially began. The Dartmouth Summer Research Project on Artificial Intelligence took place that year.

Over its eight-week period, approximately twenty participants met and worked together to discuss and conceptualize programs that could demonstrate learning capabilities. The Dartmouth Summer Research Project is often marked as the initial jumping-off point for modern developments in AI, even if the eight-week event served more as a brainstorming session. Programs developed in subsequent years taught strategies for checkers, how to speak English, and how to solve word problems.

The US Department of Defense began heavily funding AI research in the 1960s. Herbert A. Some researchers, such as Simon, claimed that within twenty years, AI could do anything a human could do. However, this prediction did not bear fruit, mainly due to computer storage limitations, and funding dwindled in the mid-1970s. Research funding rebounded in the 1980s but crashed again in the latter part of the decade.

The 1990s saw another resurgence of research, this time focused on more specialized and focused AI designed to solve specific problems. This allowed researchers to more easily demonstrate success as their AI produced tangible results in the fields of economics and statistics.

The increasing speed of computers, combined with access to the Internet and big data, allowed further advances in machine learning in the early 2010s. As of 2015, Google was using AI in more than 2,700 projects.

The current landscape

Today, AI research looks a lot different than it did in its early years. Early research often focused on artificial general intelligence. People imagine this type of AI as human-like, capable of learning any task a human can do. If you read or watch science fiction media, this type of AI is featured.

Instead, many of today’s AI researchers focus on production Artificial intelligence to complete specific tasks. For example, deep learning is a form of machine learning that relies on large amounts of data and can mimic how humans acquire knowledge. People and businesses can use deep learning for purposes such as speech or image recognition, recommendation systems, creating art, advertising, investing, fraud detection and more.

Artificial general intelligence research is now often considered a separate topic from AI designed for specific tasks.

Current AI products

If you’ve been near a TV in the past few months, you’ve probably heard about Open AI’s ChatGPT. This chatbot can take the questions you ask and give you direct answers. This is a more streamlined approach to finding information online, as the chatbot gives you instant answers instead of a list of websites that might give you conflicting information.

OpenAI is not yet developed ChatGPT Enough to change journalists and people who write for a living. However, the technology has enormous potential and will fundamentally change many different sectors.

You may have seen many people using another AI product last year called Lensa. Users can upload photos to the Lensa app and — for a fee — receive slightly touched-up, animated pictures of themselves to use as profile pictures for Instagram or Twitter. Although this is a fairly redundant use for AI, it shows how ubiquitous it is becoming.

There are also many companies using AI for more practical purposes. Retailers can use AI to learn where their supply chain is weak or demand is low and adjust accordingly. Insurance companies can use AI to identify cases at risk of escalation and offer potential solutions to avoid further conflict. Customer service jobs may eventually be replaced by AI bots.

Several automated investment platforms have started Harnessing the power of AI to streamline investments to their users. With some apps, you can put money into a portfolio and have AI move your investments around to maximize profits and protect against downturns. This is especially useful since Monitor the news to decide what to invest May take time.

Limitations of Intelligence Testing and the Turing Test

A major problem with knowing when artificial general intelligence achieves sentience is that intelligence tests are incredibly limited.

In 1948, English mathematician, computer scientist and philosopher Alan Turing proposed the Turing Test. This is a primary method of determining whether an AI is intelligent.
The test requires two humans and one AI. A human, the interviewer, interacts with two subjects, one human and one AI. If the interviewer can’t decide which is human and which is AI, meaning the AI ​​is constantly fooling the interviewer into believing it, then the AI ​​is intelligent.

Most experts today agree that this test is ineffective for determining machine intelligence.

Another proposed method of measuring comprehension is the General Language Understanding Evaluation (GLUE). GLUE is like the SATs for AI, asking programs to answer English-language questions based on datasets of varying sizes.

However, GLUE benchmarks and similar tests also have limitations. Many would argue that animals like cats and dogs can think and feel, the basic requirements for sentience. However, how many pet dogs can manage to pass a multiple choice test?

Also, with new developments featuring ChatGPT Natural Language Processing (NLP) capabilities, it is clear that some AI programs can process language. However, most people would agree that it is not the same as receiving a spirit.

How do we know if AI is sentient?

Given the limitations of current tests to determine sentience, how will we ultimately know if a machine has acquired the ability to both think and feel?

The truth is, given our current understanding of consciousness, it would be difficult and may not be possible. There is no consensus on precisely determining whether AI is conscious.

Research on tests that can prove sentience as well as the science of consciousness continues. Future advances may provide us with answers that we can use to more precisely define and test senescence.

Will AI ever be sentient?

Another topic to consider is whether it is possible for artificial intelligence to acquire sentience as well. Sentient AI is a popular topic in science fiction, but can it ever become a reality?

Experts have taken a mixed position on the subject. A former Google engineer, Blake Lemoine, claimed that AI has already acquired sentience through the Language Model for Dialogue Applications (LaMDA) chat program. In a conversation with the program, Lemoine claimed to have felt sad while reading the program Les Miserables And was afraid of death.

Google argued that the claims were completely unfounded and fired Lemoine last year.

On the other hand, John Bassal, an associate professor at Northeastern University’s College of Social Sciences and Humanities who researches the ethics of emerging technologies, believes, “Reactions like ‘we’ve created sentient AI’ are wildly overblown.”

In an article for Northeastern, Basel elaborates that he expects that if an AI ever achieves sentience, it will be only minimally conscious. It may be aware of what is happening and have basic positive or negative emotions, like a dog that “does not in any deep sense prefer the world to be one way over another, but clearly prefers to kibble its biscuits.”

Even researchers who believe in the potential of AI sentience debate whether it’s a good idea to pursue it. It’s not hard to find people speculating about various worst-case scenarios in which nefarious actors create millions or even billions of bots to force a destructive political agenda on us. Anyone who has seen it Matrix familiar with media in which AI-enhanced machines supersede humans and eventually replace us as the dominant life form.

Whether or not that is nonsense or a possible future reality remains to be seen. Technology has evolved a lot in the last decade and it is difficult to predict where it will be in the future.

The bottom line

Artificial intelligence is an exciting field that has interested humans in one form or another since ancient times. However, in the last few decades it has only become an area that people interact with on a daily basis.

Despite the many questions surrounding the field, the fact that AI can fulfill many complex tasks cannot be hidden. Companies ranging from insurance providers to retailers have started using AI to optimize their work.

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