Mediaboss Marketing

What Is Artificial Intelligence (AI)?

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.

The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal.

When most people hear the term artificial intelligence, the first thing they usually think of is robots. That's because big-budget films and novels weave stories about human-like machines that wreak havoc on Earth. But nothing could be further from the truth.

Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the most simple to those that are even more complex. The goals of artificial intelligence include learning, reasoning, and perception.

As technology advances, previous benchmarks that defined artificial intelligence become outdated. For example, machines that calculate basic functions or recognize text through optimal character recognition are no longer considered to embody artificial intelligence, since this function is now taken for granted as an inherent computer function.

AI is continuously evolving to benefit many different industries. Machines are wired using a cross-disciplinary approach based in mathematics, computer science, linguistics, psychology,and more.

Algorithms often play a very important part in the structure of artificial intelligence, where simple algorithms are used in simple applications, while more complex ones help frame strong artificial intelligence.

The applications for artificial intelligence are endless. The technology can be applied to many different sectors and industries. AI is being tested and used in the healthcare industry for dosing drugs and different treatment in patients, and for surgical procedures in the operating room.

Other examples of machines with artificial intelligence include computers that play chess and self-driving cars. Each of these machines must weigh the consequences of any action they take, as each action will impact the end result. In chess, the end result is winning the game. For self-driving cars, the computer system must account for all external data and compute it to act in a way that prevents a collision.

Artificial intelligence also has applications in the financial industry, where it is used to detect and flag activity in banking and finance such as unusual debit card usage and large account depositsall of which help a bank's fraud department. Applications for AI are also being used to help streamline and make trading easier. This is done by making supply, demand, and pricing of securities easier to estimate.

Artificial intelligence can be divided into two different categories: weak and strong. Weak artificial intelligence embodies a system designed to carry out one particular job. Weak AI systems include video games such as the chess example from above and personal assistants such as Amazon's Alexa and Apple's Siri. You ask the assistant a question, it answers it for you.

Strong artificial intelligence systems are systems that carry on the tasks considered to be human-like. These tend to be more complex and complicated systems. They are programmed to handle situations in which they may be required to problem solve without having a person intervene. These kinds of systems can be found in applications like self-driving cars or in hospital operating rooms.

Since its beginning, artificial intelligence has come under scrutiny from scientists and the public alike. One common theme is the idea that machines will become so highly developed that humans will not be able to keep up and they will take off on their own, redesigning themselves at an exponential rate.

Another is that machines can hack into people's privacy and even be weaponized.Other arguments debate the ethics of artificial intelligence and whether intelligent systems such as robots should be treated with the same rights as humans.

Self-driving cars have been fairly controversial as their machines tend to be designed for the lowest possible risk and the least casualties. If presented with a scenario of colliding with one person or another at the same time, these cars would calculate the option that would cause the least amount of damage.

Another contentious issue many people have with artificial intelligence is how it may affect human employment. With many industries looking to automate certain jobs through the use of intelligent machinery, there is a concern that people would be pushed out of the workforce. Self-driving cars may remove the need for taxis and car-share programs, while manufacturers may easily replace human labor with machines, making people's skills more obsolete.

See the original post here:
Artificial Intelligence (AI) Definition

Few concepts are as poorly understood as artificial intelligence. Opinion surveys show that even top business leaders lack a detailed sense of AI and that many ordinary people confuse it with super-powered robots or hyper-intelligent devices. Hollywood helps little in this regard by fusing robots and advanced software into self-replicating automatons such as the Terminators Skynet or the evil HAL seen in Arthur Clarkes 2001: A Space Odyssey, which goes rogue after humans plan to deactivate it. The lack of clarity around the term enables technology pessimists to warn AI will conquer humans, suppress individual freedom, and destroy personal privacy through a digital 1984.

Part of the problem is the lack of a uniformly agreed upon definition. Alan Turing generally is credited with the origin of the concept when he speculated in 1950 about thinking machines that could reason at the level of a human being. His well-known Turing Test specifies that computers need to complete reasoning puzzles as well as humans in order to be considered thinking in an autonomous manner.

Turing was followed up a few years later by John McCarthy, who first used the term artificial intelligence to denote machines that could think autonomously. He described the threshold as getting a computer to do things which, when done by people, are said to involve intelligence.

Since the 1950s, scientists have argued over what constitutes thinking and intelligence, and what is fully autonomous when it comes to hardware and software. Advanced computers such as the IBM Watson already have beaten humans at chess and are capable of instantly processing enormous amounts of information.

The lack of clarity around the term enables technology pessimists to warn AI will conquer humans, suppress individual freedom, and destroy personal privacy through a digital 1984.

Today, AI generally is thought to refer to machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment, and intention. According to researchers Shubhendu and Vijay, these software systems make decisions which normally require [a] human level of expertise and help people anticipate problems or deal with issues as they come up. As argued by John Allen and myself in an April 2018 paper, such systems have three qualities that constitute the essence of artificial intelligence: intentionality, intelligence, and adaptability.

In the remainder of this paper, I discuss these qualities and why it is important to make sure each accords with basic human values. Each of the AI features has the potential to move civilization forward in progressive ways. But without adequate safeguards or the incorporation of ethical considerations, the AI utopia can quickly turn into dystopia.

Artificial intelligence algorithms are designed to make decisions, often using real-time data. They are unlike passive machines that are capable only of mechanical or predetermined responses. Using sensors, digital data, or remote inputs, they combine information from a variety of different sources, analyze the material instantly, and act on the insights derived from those data. As such, they are designed by humans with intentionality and reach conclusions based on their instant analysis.

An example from the transportation industry shows how this happens. Autonomous vehicles are equipped with LIDARS (light detection and ranging) and remote sensors that gather information from the vehicles surroundings. The LIDAR uses light from a radar to see objects in front of and around the vehicle and make instantaneous decisions regarding the presence of objects, distances, and whether the car is about to hit something. On-board computers combine this information with sensor data to determine whether there are any dangerous conditions, the vehicle needs to shift lanes, or it should slow or stop completely. All of that material has to be analyzed instantly to avoid crashes and keep the vehicle in the proper lane.

With massive improvements in storage systems, processing speeds, and analytic techniques, these algorithms are capable of tremendous sophistication in analysis and decisionmaking. Financial algorithms can spot minute differentials in stock valuations and undertake market transactions that take advantage of that information. The same logic applies in environmental sustainability systems that use sensors to determine whether someone is in a room and automatically adjusts heating, cooling, and lighting based on that information. The goal is to conserve energy and use resources in an optimal manner.

As long as these systems conform to important human values, there is little risk of AI going rogue or endangering human beings. Computers can be intentional while analyzing information in ways that augment humans or help them perform at a higher level. However, if the software is poorly designed or based on incomplete or biased information, it can endanger humanity or replicate past injustices.

AI often is undertaken in conjunction with machine learning and data analytics, and the resulting combination enables intelligent decisionmaking. Machine learning takes data and looks for underlying trends. If it spots something that is relevant for a practical problem, software designers can take that knowledge and use it with data analytics to understand specific issues.

For example, there are AI systems for managing school enrollments. They compile information on neighborhood location, desired schools, substantive interests, and the like, and assign pupils to particular schools based on that material. As long as there is little contentiousness or disagreement regarding basic criteria, these systems work intelligently and effectively.

Figuring out how to reconcile conflicting values is one of the most important challenges facing AI designers. It is vital that they write code and incorporate information that is unbiased and non-discriminatory. Failure to do that leads to AI algorithms that are unfair and unjust.

Of course, that often is not the case. Reflecting the importance of education for life outcomes, parents, teachers, and school administrators fight over the importance of different factors. Should students always be assigned to their neighborhood school or should other criteria override that consideration? As an illustration, in a city with widespread racial segregation and economic inequalities by neighborhood, elevating neighborhood school assignments can exacerbate inequality and racial segregation. For these reasons, software designers have to balance competing interests and reach intelligent decisions that reflect values important in that particular community.

Making these kinds of decisions increasingly falls to computer programmers. They must build intelligent algorithms that compile decisions based on a number of different considerations. That can include basic principles such as efficiency, equity, justice, and effectiveness. Figuring out how to reconcile conflicting values is one of the most important challenges facing AI designers. It is vital that they write code and incorporate information that is unbiased and non-discriminatory. Failure to do that leads to AI algorithms that are unfair and unjust.

The last quality that marks AI systems is the ability to learn and adapt as they compile information and make decisions. Effective artificial intelligence must adjust as circumstances or conditions shift. This may involve alterations in financial situations, road conditions, environmental considerations, or military circumstances. AI must integrate these changes in its algorithms and make decisions on how to adapt to the new possibilities.

One can illustrate these issues most dramatically in the transportation area. Autonomous vehicles can use machine-to-machine communications to alert other cars on the road about upcoming congestion, potholes, highway construction, or other possible traffic impediments. Vehicles can take advantage of the experience of other vehicles on the road, without human involvement, and the entire corpus of their achieved experience is immediately and fully transferable to other similarly configured vehicles. Their advanced algorithms, sensors, and cameras incorporate experience in current operations, and use dashboards and visual displays to present information in real time so human drivers are able to make sense of ongoing traffic and vehicular conditions.

A similar logic applies to AI devised for scheduling appointments. There are personal digital assistants that can ascertain a persons preferences and respond to email requests for personal appointments in a dynamic manner. Without any human intervention, a digital assistant can make appointments, adjust schedules, and communicate those preferences to other individuals. Building adaptable systems that learn as they go has the potential of improving effectiveness and efficiency. These kinds of algorithms can handle complex tasks and make judgments that replicate or exceed what a human could do. But making sure they learn in ways that are fair and just is a high priority for system designers.

In short, there have been extraordinary advances in recent years in the ability of AI systems to incorporate intentionality, intelligence, and adaptability in their algorithms. Rather than being mechanistic or deterministic in how the machines operate, AI software learns as it goes along and incorporates real-world experience in its decisionmaking. In this way, it enhances human performance and augments peoples capabilities.

Of course, these advances also make people nervous about doomsday scenarios sensationalized by movie-makers. Situations where AI-powered robots take over from humans or weaken basic values frighten people and lead them to wonder whether AI is making a useful contribution or runs the risk of endangering the essence of humanity.

With the appropriate safeguards,countries can move forward and gain the benefits of artificial intelligence and emerging technologies without sacrificing the important qualities that define humanity.

There is no easy answer to that question, but system designers must incorporate important ethical values in algorithms to make sure they correspond to human concerns and learn and adapt in ways that are consistent with community values. This is the reason it is important to ensure that AI ethics are taken seriously and permeate societal decisions. In order to maximize positive outcomes, organizations should hire ethicists who work with corporate decisionmakers and software developers, have a code of AI ethics that lays out how various issues will be handled, organize an AI review board that regularly addresses corporate ethical questions, have AI audit trails that show how various coding decisions have been made, implement AI training programs so staff operationalizes ethical considerations in their daily work, and provide a means for remediation when AI solutions inflict harm or damages on people or organizations.

Through these kinds of safeguards, societies will increase the odds that AI systems are intentional, intelligent, and adaptable while still conforming to basic human values. In that way, countries can move forward and gain the benefits of artificial intelligence and emerging technologies without sacrificing the important qualities that define humanity.

Here is the original post:
What is artificial intelligence? - Brookings

Many AI researchers roll their eyes when seeing this headline:Stephen Hawking warns that rise of robots may be disastrous for mankind. And as many havelost count of how many similar articles theyveseen.Typically, these articles are accompanied by an evil-looking robot carrying a weapon, and they suggest we should worry about robots rising up and killing us because theyve become conscious and/or evil.On a lighter note, such articles are actually rather impressive, because they succinctly summarize the scenario that AI researchers dontworry about. That scenario combines as many as three separate misconceptions: concern about consciousness, evil, androbots.

If you drive down the road, you have a subjective experience of colors, sounds, etc. But does a self-driving car have a subjective experience? Does it feel like anything at all to be a self-driving car?Although this mystery of consciousness is interesting in its own right, its irrelevant to AI risk. If you get struck by a driverless car, it makes no difference to you whether it subjectively feels conscious. In the same way, what will affect us humans is what superintelligent AIdoes, not how it subjectively feels.

The fear of machines turning evil is another red herring. The real worry isnt malevolence, but competence. A superintelligent AI is by definition very good at attaining its goals, whatever they may be, so we need to ensure that its goals are aligned with ours. Humans dont generally hate ants, but were more intelligent than they are so if we want to build a hydroelectric dam and theres an anthill there, too bad for the ants. The beneficial-AI movement wants to avoid placing humanity in the position of those ants.

The consciousness misconception is related to the myth that machines cant have goals.Machines can obviously have goals in the narrow sense of exhibiting goal-oriented behavior: the behavior of a heat-seeking missile is most economically explained as a goal to hit a target.If you feel threatened by a machine whose goals are misaligned with yours, then it is precisely its goals in this narrow sense that troubles you, not whether the machine is conscious and experiences a sense of purpose.If that heat-seeking missile were chasing you, you probably wouldnt exclaim: Im not worried, because machines cant have goals!

I sympathize with Rodney Brooks and other robotics pioneers who feel unfairly demonized by scaremongering tabloids,because some journalists seem obsessively fixated on robots and adorn many of their articles with evil-looking metal monsters with red shiny eyes. In fact, the main concern of the beneficial-AI movement isnt with robots but with intelligence itself: specifically, intelligence whose goals are misaligned with ours. To cause us trouble, such misaligned superhuman intelligence needs no robotic body, merely an internet connection this may enable outsmarting financial markets, out-inventing human researchers, out-manipulating human leaders, and developing weapons we cannot even understand. Even if building robots were physically impossible, a super-intelligent and super-wealthy AI could easily pay or manipulate many humans to unwittingly do its bidding.

The robot misconception is related to the myth that machines cant control humans. Intelligence enables control: humans control tigers not because we are stronger, but because we are smarter. This means that if we cede our position as smartest on our planet, its possible that we might also cede control.

More here:
Benefits & Risks of Artificial Intelligence - Future of ...

Artificial intelligence continues to grow rapidly. Tom Merritt breaks down the five things you need to know about AI, according to a report from Stanford University.

Every year the Human-Centered Artificial Institute at Stanford puts together the Artificial Intelligence Index Report, relying on experts from around the discipline, including folks at Harvard, Google Open AI, and more, to try to pin down where we are with artificial intelligence (AI). You should definitely read all 290 pages, but for now here are five things to know about the state of AI.

SEE: Artificial intelligence ethics policy (TechRepublic Premium)

That's just where the work is getting done and where the money flows. As far as results, AI seems to be helping make software work a little better. But, most of your human skills are just getting help from the competition, not being replaced for now.

We deliver the top business tech news stories about the companies, the people, and the products revolutionizing the planet. Delivered Daily

Image: iStockphoto/metamorworks

Read more here:
Top 5 things to know about the state of artificial intelligence - TechRepublic

We know machines and artificial intelligence (AI) can be many things, but can they ever really be creative? When I interviewed Professor Marcus du Sautoy, the author of The Creativity Code, he shared that the role of AI is a kind of catalyst to push our human creativity. Its the machine and human collaboration that produces exciting resultsnovel approaches and combinations that likely wouldnt develop if either were working alone.

Can Machines And Artificial Intelligence Be Creative?

Instead of thinking about AI as replacing human creativity, it's beneficial to examine ways that AI can be used as a tool to augment human creativity. Here are several examples of how AI boosts the creativity of humans in art, music, dance, design, recipe building, and publishing.

Art

In the world of visual art, AI is making an impact in many ways. It can alter existing art such as the case when it made the Mona Lisa a living portrait a la Harry Potter, create likenesses that appear to be real humans that can be found on the website ThisPersonDoesNotExist.com and even create original works of art.

When Christies auctioned off a piece of AI artwork titled the Portrait of Edmond de Belamy for $432,500, it became the first auction house to do so. The AI algorithm, a generative adversarial network (GAN) developed by a Paris-based collective, that created the art, was fed a data set of 15,000 portraits covering six centuries to inform its creativity.

Another development that blurs the boundaries of what it means to be an artist is Ai-Da, the worlds first robot artist, who recently held her first solo exhibition. She is equipped with facial recognition technology and a robotic arm system thats powered by artificial intelligence.

More eccentric art is also a capability of artificial intelligence. Algorithms can read recipes and create images of what the final dish will look like. Dreamscope by Google uses traditional images of people, places and things and runs them through a series of filters. The output is truly original, albeit sometimes the stuff of nightmares.

Music

If AI can enhance creativity in visual art, can it do the same for musicians? David Cope has spent the last 30 years working on Experiments in Musical Intelligence or EMI. Cope is a traditional musician and composer but turned to computers to help get past composers block back in 1982. Since that time, his algorithms have produced numerous original compositions in a variety of genres as well as created Emily Howell, an AI that can compose music based on her own style rather than just replicate the styles of yesterdays composers.

In many cases, AI is a new collaborator for todays popular musicians. Sony's Flow Machine and IBM's Watson are just two of the tools music producers, YouTubers, and other artists are relying on to churn out today's hits. Alex Da Kid, a Grammy-nominated producer, used IBMs Watson to inform his creative process. The AI analyzed the "emotional temperature" of the time by scraping conversations, newspapers, and headlines over a five-year period. Then Alex used the analytics to determine the theme for his next single.

Another tool that embraces human and machine collaboration, AIVA bills itself as a creative assistant for creative people and uses AI and deep learning algorithms to help compose music.

In addition to composing music, artificial intelligence is transforming the music industry in a variety of ways from distribution to audio mastering and even creating virtual pop stars. An auxuman singer called Yona, developed by Iranian electronica composer Ash Koosha, creates and performs music such as the song Oblivious through AI algorithms.

Dance and Choreography

A powerful way dance choreographers have been able to break out of their regular patterns is to use artificial intelligence as a collaborator. Wayne McGregor, the award-winning British choreographer and director, is known for using technology in his work and is particularly fascinated by how AI could enhance what is done with the choreography in a project with Google Arts & Culture Lab. Hundreds of hours of video footage of dancers representing individual styles were fed into the algorithm. The AI then went to work and "learned how to dance. The goal is not to replace the choreographer but to efficiently iterate and develop different choreography options.

AI Augmented Design

Another creative endeavor AI is proving to be adept at is commercial design. In a collaboration between French designer Philippe Starck, Kartell, and Autodesk, a 3D software company, the first chair designed using artificial intelligence and put into production was presented at Milan Design Week. The Chair Project is another collaboration that explores co-creativity between people and machines.

Recipes

The creativity of AI is also transforming the kitchen not only by altering longstanding recipes but also creating entirely new food combinations in collaborations with some of the biggest names in the food industry. Our favorite libations might also get an AI makeover. You can now pre-order AI-developed whiskey. Brewmasters decisions are also being informed by artificial intelligence. MITs Computer Science and Artificial Intelligence Laboratory (CSAIL) is making use of all those photos of the food that we post on social media. By using computer vision, these food photos are being analyzed to better understand peoples eating habits as well as to suggest recipes with the food that is pictured.

Write Novels and Articles

Even though the amount of written material to inform artificial intelligence algorithms is voluminous, writing has been a challenging skill for AI to acquire. Although AI has been most successful in generating short-form formulaic content such as journalism "who, what, where, and when stories," its skills continue to grow. AI has now written a novel, and although neural networks created what many might find a weird read, it was still able to do it. And, with the announcement a Japanese AI programs short-form novel almost won a national literary prize, its easy to see how it wont be long before AI can compete with humans to write compelling pieces of content. Kopan Page published Superhuman Innovation, a book not only about artificial intelligence but was co-written by AI. PoemPortraits is another example of AI and human collaboration where you can provide the algorithm with a single word that it will use to generate a short poem.

As the world of AI and human creativity continue to expand, its time to stop worrying about if AI can be creative, but how the human and machine world can intersect for creative collaborations that have never been dreamt of before.

You can watch the full interview with Marcus du Sautoy here:

View post:
Can Machines And Artificial Intelligence Be Creative? - Forbes