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Artificial Intelligence - How Is AI Contributing To Cybernetics?

The study of communication and control in live creatures and machines is known as cybernetics.

Although the phrase "cybernetic thinking" is no longer generally used in the United States, it pervades computer science, engineering, biology, and the social sciences today.

Throughout the last half-century, cybernetic connectionist and artificial neural network approaches to information theory and technology have often clashed, and in some cases hybridized, with symbolic AI methods.

Norbert Wiener (1894–1964), who coined the term "cybernetics" from the Greek word for "steersman," saw the field as a unifying force that brought disparate topics like game theory, operations research, theory of automata, logic, and information theory together and elevated them.

Winer argued in Cybernetics, or Control and Communication in the Animal and the Machine (1948), that contemporary science had become too much of a specialist's playground as a consequence of tendencies dating back to the early Enlightenment.

Wiener envisioned a period when experts might collaborate "not as minions of some great administrative officer, but united by the desire, indeed by the spiritual imperative, to comprehend the area as a whole, and to give one another the power of that knowledge" (Weiner 1948b, 3).

For Wiener, cybernetics provided researchers with access to many sources of knowledge while maintaining their independence and unbiased detachment.

Wiener also believed that man and machine should be seen as basically interchangeable epistemologically.

The biological sciences and medicine, according to Wiener, would remain semi-exact and dependent on observer subjectivity until these common components were discovered.

In the setting of World War II (1939– 1945), Wiener developed his cybernetic theory.

Operations research and game theory, for example, are interdisciplinary sciences rich in mathematics that have previously been utilized to identify German submarines and create the best feasible solutions to complex military decision-making challenges.

Wiener committed himself into the job of implementing modern cybernetic weapons against the Axis countries in his role as a military adviser.

To that purpose, Wiener focused on deciphering the feedback processes involved in curvilinear flight prediction and applying these concepts to the development of advanced fire-control systems for shooting down enemy aircraft.

Claude Shannon, a long-serving Bell Labs researcher, went even further than Wiener in attempting to bring cybernetic ideas to life, most notably in his experiments with Theseus, an electromechanical mouse that used digital relays and a feedback process to learn how to navigate mazes based on previous experience.

Shannon created a slew of other automata that mimicked the behavior of thinking machines.

Shannon's mentees, including AI pioneers John McCarthy and Marvin Minsky, followed in his footsteps and labeled him a symbolic information processor.

McCarthy, who is often regarded with establishing the field of artificial intelligence, studied the mathematical logic that underpins human thought.

Minsky opted to research neural network models as a machine imitation of human vision.

The so-called McCulloch-Pitts neurons were the core components of cybernetic understanding of human cognitive processing.

These neurons were strung together by axons for communication, establishing a cybernated system encompassing a crude simulation of the wet science of the brain, and were named after Warren McCulloch and Walter Pitts.

Pitts admired Wiener's straightforward analogy of cerebral tissue to vacuum tube technology, and saw these switching devices as metallic analogues to organic cognitive components.

McCulloch-Pitts neurons were believed to be capable of mimicking basic logical processes required for learning and memory.

Pitts perceived a close binary equivalence between the electrical discharges produced by these devices and the electrochemical nerve impulses generated in the brain in the 1940s.

McCulloch-Pitts inputs may be either a zero or a one, and the output can also be a zero or a one in their most basic form.

Each input may be categorized as excitatory or inhibitory.

It was therefore merely a short step from artificial to animal memory for Pitts and Wiener.

Donald Hebb, a Canadian neuropsychologist, made even more significant contributions to the research of artificial neurons.

These were detailed in his book The Organization of Behavior, published in 1949.

Associative learning is explained by Hebbian theory as a process of neural synaptic cells firing and connecting together.

In his study of the artificial "perceptron," a model and algorithm that weighted inputs so that it could be taught to detect particular kinds of patterns, U.S.

Navy researcher Frank Rosenblatt expanded the metaphor.

The eye and cerebral circuitry of the perceptron could approximately discern between pictures of cats and dogs.

The navy saw the perceptron as "the embryo of an electronic computer that it anticipates to be able to walk, speak, see, write, reproduce itself, and be cognizant of its existence," according to a 1958 interview with Rosenblatt (New York Times, July 8, 1958, 25).

Wiener, Shannon, McCulloch, Pitts, and other cyberneticists were nourished by the famed Macy Conferences on Cybernetics in the 1940s and 1950s, which attempted to automate human comprehension of the world and the learning process.

The gatherings also acted as a forum for discussing artificial intelligence issues.

The divide between the areas developed over time, but it was visible during the 1956 Dartmouth Summer Research Project on ArtificialIntelligence.

Organic cybernetics research was no longer well-defined in American scientific practice by 1970.

Computing sciences and technology evolved from machine cybernetics.

Cybernetic theories are now on the periphery of social and hard scientific disciplines such as cognitive science, complex systems, robotics, systems theory, and computer science, but they were critical to the information revolution of the twentieth and twenty-first centuries.

In recent studies of artificial neural networks and unsupervised machine learning, Hebbian theory has seen a resurgence of attention.

Cyborgs—beings made up of biological and mechanical pieces that augment normal functions—could be regarded a subset of cybernetics (which was once known as "medical cybernetics" in the 1960s).

~ Jai Krishna Ponnappan

You may also want to read more about Artificial Intelligence here.

Artificial Intelligence - Who Is Sherry Turkle?

Sherry Turkle(1948–) has a background in sociology and psychology, and her work focuses on the human-technology interaction.

While her study in the 1980s focused on how technology affects people's thinking, her work in the 2000s has become more critical of how technology is utilized at the expense of building and maintaining meaningful interpersonal connections.

She has employed artificial intelligence in products like children's toys and pets for the elderly to highlight what people lose out on when interacting with such things.

Turkle has been at the vanguard of AI breakthroughs as a professor at the Massachusetts Institute of Technology (MIT) and the creator of the MIT Initiative on Technology and the Self.

She highlights a conceptual change in the understanding of AI that occurs between the 1960s and 1980s in Life on the Screen: Identity inthe Age of the Internet (1995), substantially changing the way humans connect to and interact with AI.

She claims that early AI paradigms depended on extensive preprogramming and employed a rule-based concept of intelligence.

However, this viewpoint has given place to one that considers intelligence to be emergent.

This emergent paradigm, which became the recognized mainstream view by 1990, claims that AI arises from a much simpler set of learning algorithms.

The emergent method, according to Turkle, aims to emulate the way the human brain functions, assisting in the breaking down of barriers between computers and nature, and more generally between the natural and the artificial.

In summary, an emergent approach to AI allows people to connect to the technology more easily, even thinking of AI-based programs and gadgets as children.

Not just for the area of AI, but also for Turkle's study and writing on the subject, the rising acceptance of the emerging paradigm of AI and the enhanced relatability it heralds represents a significant turning point.

Turkle started to employ ethnographic research techniques to study the relationship between humans and their gadgets in two edited collections, Evocative Objects: Things We Think With (2007) and The Inner History of Devices (2008).

She emphasized in her book The Inner History of Devices that her intimate ethnography, or the ability to "listen with a third ear," is required to go past the advertising-based clichés that are often employed when addressing technology.

This method comprises setting up time for silent meditation so that participants may think thoroughly about their interactions with their equipment.

Turkle used similar intimate ethnographic approaches in her second major book, Alone Together:

Why We Expect More from Technology and Less from Each Other (2011), to argue that the increasing connection between people and the technology they use is harmful.

These issues are connected to the increased usage of social media as a form of communication, as well as the continuous degree of familiarity and relatability with technology gadgets, which stems from the emerging AI paradigm that has become practically omnipresent.

She traced the origins of the dilemma back to early pioneers in the field of cybernetics, citing, for example, Norbert Weiner's speculations on the idea of transmitting a human person across a telegraph line in his book God & Golem, Inc.(1964).

Because it reduces both people and technology to information, this approach to cybernetic thinking blurs the barriers between them.

In terms of AI, this implies that it doesn't matter whether the machines with which we interact are really intelligent.

Turkle claims that by engaging with and caring for these technologies, we may deceive ourselves into feeling we are in a relationship, causing us to treat them as if they were sentient.

In a 2006 presentation titled "Artificial Intelligence at 50: From Building Intelligence to Nurturing Sociabilities" at the Dartmouth Artificial Intelligence Conference, she recognized this trend.

She identified the 1997 Tamagotchi, 1998 Furby, and 2000 MyReal Baby as early versions of what she refers to as relational artifacts, which are more broadly referred to as social machines in the literature.

The main difference between these devices and previous children's toys is that these devices come pre-animated and ready for a relationship, whereas previous children's toys required children to project a relationship onto them.

Turkle argues that this change is about our human weaknesses as much as it is about computer capabilities.

In other words, just caring for an item increases the likelihood of not only seeing it as intelligent but also feeling a connection to it.

This sense of connection is more relevant to the typical person engaging with these technologies than abstract philosophic considerations concerning the nature of their intelligence.

Turkle delves more into the ramifications of people engaging with AI-based technologies in both Alone Together and Reclaiming Conversation: The Power of Talk in a Digital Age (2015).

She provides the example of Adam in Alone Together, who appreciates the appreciation of the AI bots he controls over in the game Civilization.

Adam appreciates the fact that he is able to create something fresh when playing.

Turkle, on the other hand, is skeptical of this interaction, stating that Adam's playing isn't actual creation, but rather the sensation of creation, and that it's problematic since it lacks meaningful pressure or danger.

In Reclaiming Conversation, she expands on this point, suggesting that social partners simply provide a perception of camaraderie.

This is important because of the value of human connection and what may be lost in relationships that simply provide a sensation or perception of friendship rather than true friendship.

Turkle believes that this transition is critical.

She claims that although connections with AI-enabledtechnologies may have certain advantages, they pale in contrast to what is missing:

the complete complexity and inherent contradictions that define what it is to be human.

A person's connection with an AI-enabled technology is not as intricate as one's interaction with other individuals.

Turkle claims that as individuals have become more used to and dependent on technology gadgets, the definition of friendship has evolved.

People's expectations for companionship have been simplified as a result of this transformation, and the advantages that one wants to obtain from partnerships have been reduced.

People now tend to associate friendship only with the concept of interaction, ignoring the more nuanced sentiments and arguments that are typical in partnerships.

By engaging with gadgets, one may form a relationship with them.

Conversations between humans have become merely transactional as human communication has shifted away from face-to-face conversation and toward interaction mediated by devices.

In other words, the most that can be anticipated is engagement.

Turkle, who has a background in psychoanalysis, claims that this kind of transactional communication allows users to spend less time learning to view the world through the eyes of another person, which is a crucial ability for empathy.

Turkle argues we are in a robotic period in which people yearn for, and in some circumstances prefer, AI-based robotic companionship over that of other humans, drawing together these numerous streams of argument.

For example, some people enjoy conversing with their iPhone's Siri virtual assistant because they aren't afraid of being judged by it, as evidenced by a series of Siri commercials featuring celebrities talking to their phones.

Turkle has a problem with this because these devices can only respond as if they understand what is being said.

AI-based gadgets, on the other hand, are confined to comprehending the literal meanings of data stored on the device.

They can decipher the contents of phone calendars and emails, but they have no idea what any of this data means to the user.

There is no discernible difference between a calendar appointment for car maintenance and one for chemotherapy for an AI-based device.

A person may lose sight of what it is to have an authentic dialogue with another human when entangled in a variety of these robotic connections with a growing number of technologies.

While Reclaiming Communication documents deteriorating conversation skills and decreasing empathy, it ultimately ends on a positive note.

Because people are becoming increasingly dissatisfied with their relationships, there may be a chance for face-to-face human communication to reclaim its vital role.

Turkle's ideas focus on reducing the amount of time people spend on their phones, but AI's involvement in this interaction is equally critical.

Users must accept that their virtual assistant connections will never be able to replace face-to-face interactions.

This will necessitate being more deliberate in how one uses devices, prioritizing in-person interactions over the faster and easier interactions provided by AI-enabled devices.

~ Jai Krishna Ponnappan

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