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Artificial intelligence (AI) has taken on many new shapes and use cases as experts learn more about whats possible with big data and smart algorithms.

Todays AI market, then, consists of a mixture of tried-and-true smart technologies with new optimizations and advanced AI that is slowly transforming the way we do work and live daily life.

Read on to learn about some artificial intelligence trends that are making experts most excited for the future of AI:

More on the AI market: Artificial Intelligence Market

With its ability to follow basic tasks and routines based on smart programming and algorithms, artificial intelligence is becoming embedded in the way organizations automate their business processes.

AIOps and MLops are common use cases for AI and automation, but the breadth and depth of what AI can automate in the enterprise is quickly growing.

Bali D.R., SVP at Infosys, a global digital services and consulting firm, believes that AI is moving toward a certain level of hyper-automation, partially in response to the unexpected changes in manual data and procedures caused by the pandemic.

We are in the second inflection point for AI as it graduates from consumer AI, towards enterprise-grade AI, D.R. said. Being exposed to an over-reliance on manual procedures, such as mass rescheduling in the airline industry, unprecedented loan applications in banks, etc., the industries are now turning to hyper-automation that combines robotic process automation with modern machine learning to ensure they can better handle surges in the future.

Although AI automation is still mostly limited to interval and task-oriented automation that requires little imagination or guesswork on the part of the tool, some experts believe we are moving closer to more applications for intelligent automation.

David Tareen, director for artificial intelligence at SAS, a top analytics and AI software company, had this to say about the future of intelligent automation:

Intelligent automation is an area I expect to grow, Tareen said. Just like we automated manufacturing work, we will use AI heavily to automate knowledge work.

The complexity comes in because knowledge work has a high degree of variability. For example, an organization will receive feedback on their products or services in different ways and often in different languages as well. AI will need to ingest, understand, and modify processes in real-time before we can automate knowledge work at large.

AI, automation, and the job market: Artificial Intelligence and Automation

Because of the depth of big data and AIs reliance on it, theres always the possibility that unethical or ill-prepared data will make it into an AI training data set or model.

As more companies recognize the importance of creating AI that conducts its operations in a compliant and ethical manner, a number of AI developers and service providers are starting to offer responsible AI solutions to their customers.

Read Maloney, SVP of marketing at H2O.ai, a top AI and hybrid cloud company, explained what exactly responsible AI is and some of the different initiatives that companies are undertaking to improve their AI ethics.

AI creates incredible new opportunities to improve the lives of people around the world, Maloney said. We take the responsibility to mitigate risks as core to our work, so building fairness, interpretability, security, and privacy into our AI solutions is key.

Maloney said the market is seeing an increased adoption of the core pillars of responsible AI, which he shared with Datamation:

Companies are exploring several ways to make their AI more responsible, and most are starting with cleaning and assessing both data sets and existing AI models.

Brian Gilmore, director of IoT product management at InfluxData, a database solutions company, believes that one of the top options for model and data set management is distributed ledger technology (DLT).

As attention builds around the ethical and cultural impact of AI, some organizations are beginning to invest in ancillary but important technologies that utilize consensus and other trust-ensuring systems as a part of the AI framework, Gilmore said. For example, distributed ledger technology provides a sidecar platform for auditable proof of integrity for models and training data.

The decentralized ownership, distribution of access, and shared accountability of DLT can bring significant transparency to AI development and application across the board. The dilemma is whether for-profit corporations are willing to participate in a community model, trading transparency for consumer trust in something as mission critical as AI.

See more: The Ethics of Artificial Intelligence (AI)

Up to this point, AI has most frequently been used to optimize business processes and automate some home routines for consumers.

However, some experts are beginning to realize the potential that AI-powered models can have for solving global issues.

Read Maloney at H2O.ai has worked with people from a variety of industries to brainstorm how AI can be used for the greater good.

We work with many like-minded customers, partners, and organizations tackling issues from education, conservation, health care, and more, Maloney said. AI for good is fundamental to not only our work, including current work on climate change, wildfires, and hurricane predictions, but we are seeing more and more AI for good work to make the world a better place across the AI industry.

Some of the most exciting applications of altruistic AI are being implemented in early education right now.

For instance, Helen Thomas, CEO ofDMAI, an AI-powered health care and education company, offers an AI-powered product to ensure that preschool-aged children are getting the education they need, despite potential pandemic setbacks:

On top of pre-existing barriers to preschool education, including cost and access, recent research findings suggest children born during the COVID-19 pandemic display lower IQ scores than those born before January 2020, which means toddlers are less prepared for school than ever before.

DMAI DBA Animal Island Learning Adventure (AILA) is changing this with AI. [Our product] harnesses cognitive AI to deliver appropriate lessons in a consistent and repetitious format, supportive of natural learning patterns

Recognizing learning patterns that parents might miss, the AI creates an adaptive learning journey and doesnt allow the child to move forward until theyve mastered the skills and concepts presented. This intentional delivery also increases attention span over time, ensuring children step into the classroom with the social-emotional intelligence to succeed.

More on this topic: How AI is Being Used in Education

Internet of Things (IoT) devices have become incredibly widespread among both enterprise and personal users, but what many tech companies still struggle with is how to gather actionable insights from the constant inflow of data from these devices.

AIoT, or the idea of combining artificial intelligence with IoT products, is one field that is starting to address these pools of unused data, giving AI the power to translate that data quickly and intelligently.

Bill Scudder, SVP and AIoT general manager at AspenTech, an industrial AI solutions company, believes that AIoT is one of the most crucial fields for enabling more intelligent, real-time business decisions.

Forrester has noted that up to 73% of all data collected within the enterprise goes unused, which highlights a critical challenge with IoT, Scudder said. As the volume of connected devices for example, in industrial IoT settings continues to increase, so does the volume of data collected from these devices.

This has resulted in a trend seen across many industries: the need to marry AI and IoT. And heres why: where IoT allows connected devices to create and transmit data from various sources, AI can take that data one step further, translating data into actionable insights to fuel faster, more intelligent business decisions. This is giving way to the rising trend of artificial intelligence of things or AIoT.

Decision intelligence (DI) is one of the newest artificial intelligence concepts that takes many current business optimizations a step farther, by using AI models to analyze wide-ranging sets of commercial data. These analyses are used to predict future outcomes for everything from products to customers to supply chains.

Sorcha Gilroy, data science team lead at Peak, a commercial AI solutions provider, explained that although decision intelligence is a fairly new concept, its already gaining traction with larger enterprises because of its detailed business intelligence (BI) offerings.

Decision intelligence is a new category of software that facilitates the commercial application of artificial intelligence, providing predictive insight and recommended actions to users, Gilroy said. It is outcome focused, meaning a solution must deliver against a business need before it can be classed as DI.

Recognized by Gartner and IDC, it has the potential to be the biggest software category in the world and is already being utilized by businesses across a variety of use cases, from personalizing shopper experiences to streamlining complex supply chains. Brands such as Nike, PepsiCo, and ASOS are known to be using DI already.

Read next: Top Performing Artificial Intelligence Companies

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Artificial Intelligence Trends & Predictions for 2022 | Datamation

Many have suggested that AI-based algorithms represent the greatest current opportunity for human progress. But their unpredictability represents the greatest threat as well, and it has not been precisely clear what steps should be taken by us as end users. Kartik Hosanagar, John C. Hower Professor; Professor of Operations, Information, and Decisions, The Wharton School

Artificial Intelligence for Business is an online program for learners seeking the competitive edge in emerging business technology. Technology-oriented professionals, online marketers, statisticians, automation innovators and data professionals will benefit from this 4-week certificate.

In the artificial intelligence course, youll learn the fundamentals of Big Data, Artificial Intelligence, and Machine Learning, and how to deploy these technologies to support your organizations strategy. Professor Kartik Hosanagar of the Wharton School has designed this course to help you gain a better understanding of AI and Machine Learning, using real-life examples. Youll learn about the different types and methods of Machine Learning, and how businesses have applied Machine Learning successfully. Youll also cover the ethics and risks of AI in business management, and how to design governance frameworks for proper implementation. By the end of this course, youll have a foundational understanding of artificial intelligence in business and be able to incorporate these technologies into your business strategy.

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Artificial Intelligence (AI) for Business Course Wharton

The Internal Revenue Service unveiled a new artificial intelligence system it says will cut wait times to resolve simple tasks and improve customer service.

The technology enables the new phone system to authenticate callers by asking them basic questions, IRS officials said during a call with reporters Friday. The new system can understand complete and natural ways of speaking, they said.

For the first time in 160 years, this agency is able to successfully interact with a taxpayer using artificial intelligence to access their account and resolve it, in certain situations, without any wait on hold, IRS Deputy Commissioner Darren Guillot said during the call.

When taxpayers receive a mailed letter stating they owe money, they can use an ID number from the letter to call in and access the improved system, agency officials explained.

Frederick Schindler, the agency's director of collection, said his team staggered the generation and mailing of over 3 million letters so they will arrive in mailboxes in the coming days, enabling callers to make use of the new system.

In this photo illustration an IRS logo seen displayed on a smartphone.

SOPA Images/LightRocket via Getty Images, FILE

The IRS efforts to improve its phone system come roughly three months after the statutory body said it would hire 10,000 additional employees to cut through a pandemic-related backlog.

Expanding the phone bot with artificial intelligence demonstrates an improvement over the previous phone system, the IRS officials said. The previous unauthenticated phone bot could only answer basic questions and allowed callers to set up one-time payments, they said.

That more basic technology, which does not allow the system to pull up a person's IRS account, is also the technology behind an online chatbox the agency uses.

Because of the authentication capability of the new bot, it can access a callers IRS account. From there, callers can discuss and set up a payment plan with the bot without spending time on hold a process that would typically take 17-20 minutes with a human operator, IRS officials said.

By allowing the phone bot to handle more simple issues, it frees up human operators for more complex matters, the IRS officials said.

Treasury Department Deputy Secretary Wally Adeyemo recently told ABC News that the IRS received over 200 million calls and only had 15,000 people to answer those calls last year.

Even with the intelligent phone bot, callers will still have the option to speak with a human for additional support, IRS officials said.

Many callers owe less than $25,000, and can name their price, or the monthly amount they will commit to paying. The artificial intelligence system then computes that amount to determine whether it falls within the agency's deadline for repayment.

The Internal Revenue Service building is seen in Washington, D.C, April 5, 2022.

Stefani Reynolds/AFP via Getty Images, FILE

The new bot will not guide callers to pay more than the price they name, the officials explained.

While officials on the call admitted the new phone bot will offer a return on investment through expanded compliance, he said increasing government revenue was not the primary focus of developing the system.

Service is part of our name, Guillot said. This is all about the taxpayer experience, helping customers, he said later.

But not all callers will enjoy the no-wait time the authenticated phone bot offers. It launched only on the automated collection system and accounts management phone lines Tuesday, the IRS officials said.

For now, it is operating at 25% of its intended capacity, which saw the bot answer over 13,000 calls Thursday. The IRS plans to bring more of the system online through the end of next week, IRS officials said.

We have phone lines to deal with specific issues like liens or settlement proposals, Schindler said. In the future, theres use cases for taking this technology, particularly as we learn more about it, to any one of our collection processes.

The bot currently operates in English and Spanish, with IRS officials hoping to expand its language offerings in the future, they said.

More immediate expansion plans include programming the authenticated bot to ask questions of callers who name their monthly payments to ensure it is within their financial means, the officials said.

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IRS rolls out artificial intelligence to help callers make payments ...

Due to hype and popular fiction, the dangers of artificial intelligence (AI) are typically associated in the public eye with Sci-Fi horror scenarios. These often involve killer robots and hyper-intelligent computer systems which consider humanity a nuisance that needs to be gotten rid of for the good of the planet. While nightmares like this often play out as overblown and silly in comic books and on-screen, the risks of artificial intelligence cannot be dismissed so lightly and AI dangers do exist.

In this article, well be looking at some of the real risks of artificial intelligence, and why AI is dangerous when looked at in certain contexts or wrongly applied.

Artificial intelligence encompasses a range of technologies and systems ranging from Googles search algorithms, through smart home gadgets, to military-grade autonomous weapons. So issuing a blanket confirmation or denial to the question Is Artificial Intelligence Dangerous? isnt that simple the issue is much more nuanced than that.

Most artificial intelligence systems today qualify as weak or narrow AI technologies designed to perform specific tasks such as searching the internet, responding to environmental changes like temperature, or facial recognition. Generally speaking, narrow AI performs better than humans at those specific tasks.

For some AI developers, however, the Holy Grail is strong AI or artificial general intelligence (AGI), a level of technology at which machines would have a much greater degree of autonomy and versatility, enabling them to outperform humans in almost all cognitive tasks.

While the super intelligence of strong AI has the potential to help us eradicate war, disease, and poverty, there are significant dangers of artificial intelligence at this level. However, there are those who question whether strong AI will ever be achieved, and others who maintain that if and when it does arrive, it can only be beneficial.

Optimism aside, the increasing sophistication of technologies and algorithms may have the result that AI is dangerous if its goals and implementation run contrary to our own expectations or objectives. The risks of AI in this context may hold even at the level of narrow or weak AI. If, for example, a home or in-vehicle thermostat system is poorly configured or hacked, its operation could pose a serious hazard to human health through over-heating or freezing. The same would apply to smart city management systems or autonomous vehicle steering mechanisms.

Most researchers agree that a strong or AGI system would be unlikely to exhibit human emotions such as love or hate, and would therefore not pose AI dangers through benevolent or malevolent intentions. However, even the strongest AI must be programmed by humans initially, and its in this context that the danger lies. Specifically, artificial intelligence analysts highlight two scenarios where the underlying programming or human intent of a system design could cause problems:

This threat covers all existing and future autonomous weapons systems (military drones, robots, missile defenses, etc.), or technologies capable of intentionally or unintentionally causing massive harm or physical destruction due to misuse, hacking, or sabotage.

Besides the prospect of an AI arms race and the possibility of AI-enabled warfare in the case of autonomous weaponry, there are AI risks posed by the design and deployment of the technology itself. With high stakes activity an inherent part of military design, such systems would probably have fail-safes that make them extremely difficult to deactivate once started and their human owners could conceivably lose control of them, in escalating situations.

The classic illustration of this AI danger comes in the example of a self-driving car. If you ask such a vehicle to take you to the airport as quickly as possible, it could quite literally do so breaking every traffic law in the book, causing accidents, and freaking you out completely, in the process.

At the super intelligence level of AGI, imagine a geo-engineering or climate control system thats given free rein to implement its programming in the most efficient manner possible. The damage it could cause to infrastructure and ecosystems could be catastrophic.

How dangerous is AI? At its current rate of development, artificial intelligence has already exceeded the expectations of many observers, with milestones having been achieved that were considered decades away, just a few years ago.

While some experts still estimate that the development of human-level AI is still centuries away, most researchers are coming round to the opinion that it could happen before 2060. And the prevailing view amongst all observers is that, as long as were not 100% sure that artificial general intelligence wont happen this century, its a good idea to start safety research now, to prepare for its arrival.

Many of the safety problems associated with super intelligent AI are so complex that they may require decades to solve. A super intelligent AI will, by definition, be very good at achieving its goals whatever they may be. As humans, well need to ensure that its goals are completely aligned with ours. The same holds for weaker artificial intelligence systems as the technology continues to evolve.

Intelligence enables control, and as technology becomes smarter, the greatest danger of artificial intelligence lies in its capacity to exceed human intelligence. Once that milestone is achieved, we run the danger of losing our control over the technology. And this danger becomes even more severe if the goals of that technology dont align with our own objectives.

A scenario whereby an AGI whose goals run counter to our own uses the internet to enforce the implementation of its internal directives illustrates why AI is dangerous in this respect. Such a system could potentially impact the financial markets, manipulate social and political discourse, or introduce technological innovations that we can barely imagine, much less keep up with.

The keys to determining why artificial intelligence is dangerous or not lie in its underlying programming, the method of its deployment, and whether or not its goals are in alignment with our own.

As technology continues its march toward artificial general intelligence, AI has the potential to become more intelligent than any human, and we currently have no way of predicting how it will behave. What we can do is everything in our power to ensure that the goals of that intelligence remain compatible with ours and the research and design to implement systems that keep them that way.

Summary:

Artificial intelligence encompasses a range of technologies and systems ranging from Googles search algorithms, through smart home gadgets, to military-grade autonomous weapons. So issuing a blanket confirmation or denial to the question Is Artificial Intelligence Dangerous? isnt that simple. For some AI developers, the Holy Grail is strong AI or artificial general intelligence (AGI), a level of technology at which machines would have a much greater degree of autonomy and versatility, enabling them to outperform humans in almost all cognitive tasks. While the super intelligence of strong AI has the potential to help us eradicate war, disease, and poverty, there are significant dangers of artificial intelligence at this level. The keys to determining why artificial intelligence is dangerous or not lie in its underlying programming, the method of its deployment, and whether or not its goals are in alignment with our own.

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Dangers & Risks of Artificial Intelligence - ITChronicles

With the IU and LSBU (London South Bank University) dual degree track, you get a unique opportunity you can choose if you want to graduate with both a German and a British graduation certificate, without any extra academic requirements. The study programmes at IU and at LSBU are coordinated and therefore equivalent to each other.

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Master in Artificial Intelligence Online | IU International