Artificial intelligene is making all business operations more intelligent. Source: Shutterstock

ENTERPRISE technology has reached a new high as business leaders are not only making an effort to understand things like cloud computing, artificial intelligence, and the internet of things but are also making related and relevant investments.

As we enter a new decade, Frost & Sullivan believes that more organizations will start to sharpen their focus on artificial intelligence and aim to really unleash its full potential.

The analyst firms ICT APAC VP Richard Wong believes that artificial intelligence will be the game-changing technology that organizations must leverage to ensure their long-term sustainability.

According to Wong, there is already a pervasive adoption of artificial intelligence across industries such as manufacturing, healthcare, retail, and the public sector.

Early success in those industries is likely to further influence the examination of new applications of the technology to enhance competitiveness in todays digital age.

Value creation from artificial intelligence will remain a priority. It is important to note that any artificial intelligence implementation should be outcome-focused, leveraging the right data sets to create value, Wong told delegates at its APAC ICT Outlook conference in Singapore recently.

Despite the optimistic forecast, Frost & Sullivan believes that numerous challenges remain in the journey to get more out of the technology.

Artificial intelligence is one of the few technologies that require a multi-disciplinary approach, addressing areas such as sociology and philosophy to ensure success. In its current state, the technology is heavily reliant on data, and hence, issues such as privacy, ethics, and governance are vital challenges that need to be addressed.

With regulators getting especially serious about how businesses capture, store, and manage data, and the transparency with which they run their operations, business leaders need to pay more attention to the basics before they can leapfrog into the future with the technology.

In the coming months, as more businesses think about deploying and scaling artificial intelligence solutions, thinking about value and maximizing value will be top of mind.

Failing to dial into the technology and unleash its full potential equals failing to get the most out of the investment. Thats the reality and business leaders understand that.

Soumik Roy | @soumikroy

Soumik Roy is a business and technology specialist. He helps small and medium enterprise owners understand what's most important to their company's growth and success.

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Frost & Sullivan: Value creation from artificial intelligence remains a priority - Tech Wire Asia

As access to healthcare professionals (HCPs) declines, the challenges facing sales representatives continue to increase: less time with HCPs, Sunshine Act restrictions, and integration of practices into larger health systems. It can be daunting.

Once, influence was based on interactions between reps and HCPs more than just about anything else. But today, influence is spread across a variety of touch points, many digital, which can be accessed by an HCP at any time and place. To reinforce their value, sales reps are expected to have deep knowledge of the market and their customers, so that they can tailor their interactions to the unique needs of each.

How can todays rep succeed? Its all about data.

Data gathered judiciously, digested accurately, analysed rapidly, and used wisely makes the sales force more efficient and productive. This concept is nothing new: it dates back to the beginnings of CRM in the 20th century.

But todays digital world offers new possibilities, enabling connections and predictions that yesterdays rep never even dreamed of.

What if reps could anticipate relevance?

By combining the best in industry expertise, brand strategy, CRM technology, and artificial intelligence (AI) and machine learning, reps can have the tools to make anticipated relevance possible.

At a recent Digital Health Coalition Midwest Summit, Intouch demonstrated examples of what this could look like for a brand, using their AI assistant, EVA, which is short for embedded virtual assistant.

How does it work?

EVA connects with Veeva to access a reps calendar of appointments to obtain information about where they need to go and who they need to see. Combined with marketing segmentation, EVA tells a sales rep the segmentation of todays calls. Data further informs the conversation with helpful facts like script-writing history, marketing plan, prior messages presented, and online activity, giving our rep a prediction of what their next best actions should be. These suggestions can be offered through the voice assistant, or sent by text or email for later reference, and can power the flow of the in-office detail. After the call, EVA can help a rep record a call quickly and easily in the CRM system.

An AI-powered ecosystem makes sure no pertinent data goes to waste. Whether its an email open, a website visit, a rep conversation, a script, or any other activity, the rep can quickly and easily understand what their HCP cares about and what information will be most helpful to their practice.

By anticipating relevance, the rep can provide an HCP with information thats useful to them, in the format, time, and place that helps them most. And EVA is able to use the most relevant assets efficiently and minimise the burden of administrative tasks. Time is used wisely on both sides, making it possible for the right information to help patients that much sooner.

Want to learn more about AI and modern pharma marketing? Download Intouchs comprehensive ebook.

Interested in learning how AI can work for your reps? Reach out to the Intouch team today.

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Artificial intelligence and the future of rep visits - - pharmaphorum

Sahota Offers AI Predictions for the New Year

LOS ANGELES, Jan. 15, 2020 /PRNewswire/ --Artificial intelligence, or AI, will play a significant role in the 2020 election campaign and may also lead to major breakthroughs in solving personal medical issues, according to futurist and AI expert Neil Sahota.

"I'm increasingly concerned about the impact of fake news, photo scams and other deceits designed to negatively influence voting this year," says Sahota, who works closely with the United Nations and other organizations to foster innovation and develop next generation products/solutions to be powered by AI. "We will see the effect of more AI tools generating fraudulent information and influencing voters. Thankfully, there will also be new tools to fight this kind of disinformation. What is certain is that machine vs machine battles will become more prevalent."

The author of the influential book Own the AI Revolution (McGraw Hill), Sahota is also an IBM Master Inventor, who led the IBM Watson Group and is a professor at the University of California/Irvine.

In addition to its potential impact on the election campaigns, Sahota predicts AI will be responsible for significant medical advances. "We will see more use of AI that will accelerate solutions for doctors, nurses, clinicians and researchers in providing personalized care," he said. "Each of us is genetically unique and there isn't a one-size fits all solution for us. But AI can solve this dilemma by providing personalized medicine based on a specific person's genomic sequence, lifestyle, medical history, environment and other differences. I think there will be great strides in these areas in the coming year."

"The election and medicine are only two areas where we will feel the impact of AI, which is coming into its own as an emerging technology," Sahota says. "We are likely to see it help combine tools such as block chain, virtual reality and artificial reality. For example, I envision a virtual reality courtroom where a law student interacts with an AI 'judge,' opposing counsel and jury. AI simulation is not only more 'real world' but has great variability, meaning each time the VR module is used, it's different. There's no memorization or 'cheat sheet' for the law student. It's a dynamic, highly interactive learning module and 2020 will start the wave of convergence: combining these technologies together.

About Neil Sahota: Neil Sahota is a futurist and leading expert on Artificial Intelligence (AI) and other next generation technologies. He is the author of Own the AI Revolution (McGraw Hill) and works with the United Nations on the AI for Good initiative. Sahota is also an IBM Master Inventor, former leader of the IBM Watson Group and professor at the University of California/Irvine. His work spans multiple industries, including legal services, healthcare, life sciences, retail, travel, transportation, energy, utilities, automotive, telecommunications, media, and government.

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Artificial Intelligence Expert Neil Sahota Says AI Will Have Major Impact On 2020 Elections And In Medicine - Yahoo Finance

It may not be long before Artificial Intelligence creates access to God via modern technology, however during the 19th century, a spiritualist by the name of John Murray Spear was inspired to build a Mechanical Messiah. Born on September 16, 1804, into a deeply religious family, John Murray Spear eventually became a member and minister of the Universalist Church. He forsook his ministry for spiritualism and was aided in his endeavor by illustrious technical advisors, the members of the Association of Electrizers: Thomas Jefferson (1743 - 1826), the third president of the United States; John Quincy Adams (1767 1848) an American statesman, diplomat, and lawyer who served as the sixth president of the United States; Benjamin Rush (1746 - 1813) a signer of the United States Declaration of Independence and a civic leader in Philadelphia, and Benjamin Franklin (1706 - 1790) a scientist, journalist, politician, inventor and one of the major protagonists of the American Revolution. This ambitious project had one flaw most of the technical team were deceased.

Three of the Electricizers: John Quincy Adams ( Public Domain ); Benjamin Rush by Charles Peale (1818) ( Public Domain )and Benjamin Franklin by Joseph Duplessis (1785) ( Public Domain)

The innovative Spear, under the influence of his first wife Sophronia, was intent on bettering the fate of this wretched humanity by providing it with all sorts of 'technical' information. With the guidance of his highly qualified technical team, Spear received instructions for realizing the unattainable perpetual death; a thinking machine; an electric ship and a global telepathic network. But his greatest achievement was a strange automaton, a curious device composed of electrical and mechanical parts that was to embody the 'New Motive Force', a technological 'Holy Spirit', a new 'Messiah' destined to awaken the whole of humanity from a demonic stupor. Spear believed he was spearheading a technological revolution (certainly not yet the Fourth) at a time when electricity was just beginning to enlighten the man in the street as to what 'miracles' human ingenuity was capable of.

John Murray Spear inventor of the Mechanical Messiah

The Mechanical Messiah was not born in a stable, nor warmed by the loving breath of an ox and a donkey, as the established Christian tradition would have one believe. No, this very strange, technological transformer between the Earth and Heaven, between the Immanent and the Transcendent was born in a laboratory at High Rock Cottage, Massachusetts.

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Dr Roberto Volterri is the author of 40 books including Gli Stregoni Della Scienza

Top Image : Thetis receiving the arms of Achilles from Hephaestus by Peter Paul Rubens (1630)

Museum Boijmans Van Beuningen ( Public Domain )

By Dr Roberto Volterri

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Ancient Artificial Intelligence: The Mechanical Messiah and Other Automatons - Ancient Origins

The IoT global market revenue will reach approximately USD 1.1 trillion by 2025, predicts IDC.

IDC also says that the global IoT connections will rise with a 17 percent Compound Annual Growth Rate (CAGR) from 7 billion to 25 billion between the years 2017 to 2025.

Back in 2018, Sophia a humanoid robot performed a duet with Jimmy Fallon at his show. This performance left the audience awestruck. The entire world was spellbound of how Sophia (humanoid robot) could showcase human emotion while performing the song.

David Hanson, an American roboticist, who is the founder and Chief Executive Officer of Hanson Robotics, not only invented AI that could mirror human intelligence but also enabled it to show human emotion.

A major breakthrough in the technology world.

Well, this is just a teaser of whats coming for us.

While were here sitting in an era where science fiction is a popular genre of books has already engulfed how AI will be seen at the forefront were already living in the future thats beyond AI.

With leaps and bounds in the tech industry, AI holds a lot more in the technology world. Combining it with IoT has only further enhanced the usage of both the technologies. While IoT enables connecting two or more sensors, platforms, objects or networks to enable data transmission for several applications, AI offers the capability of analyzing the most critical information easily providing valuable insights and making highly informed decisions.

This simply means that smart AI experts will get the opportunity to bring in new IoT-enabled solutions to life.

IoT is described as the network of physical objects. For instance, these can be things that can be embedded with technologies, software or sensors that further helps in connecting or the exchange of data with other devices or systems via the internet or vice versa.

Now, these devices could be a simple ordinary household object or even sophisticated industrial tools.

There are over 8.3 billion IoT devices connected today. The growth further projects to grow to 10 billion by next year (2020) and 22 billion in 2025.

If youre wondering how AI is being used with IoT, here are a few perfect examples for you to understand.

Created by Alibaba Cloud, ET City Brain is an AI platform solution which helps in optimizing the usage of public urban resources. This has been successfully implemented in Hangzhou, China that led to a decrease in traffic by 15 percent.

The ET City Brain not only helped detect road accidents and illegal parking but also helps ambulances reach their destinations by changing the traffic signals.

Youve probably heard of the classroom monitoring system. Although this has raised certain controversy, a high school in Hangzhou, China is already making use of this system.

This camera scans the room once per 30 seconds. The algorithm is then able to determine the emotions of the student (sad, happy, angry or bored, etc.) along with their behavior such as writing, reading or raising their hand.

According to the Vice-principal of the school, its said that the system is managed locally and the behavior is focused on the entire class and not a single individual.

The data gathered is through cameras and the next step which is the image recognition step is done at the local servers.

The Tesla autopilot system enables GPS, sonars, cameras and forward-looking radars, in combination with specialized hardware, through which data can be fully utilized and coupled into Neural Network Architectures. This works like a self-enclosed system that gathers information from the sensors and further uses the Neural Network model that determines the next change in the movement of the car.

Dearth for talent and lack of expertise in the IoT market reveals the upsurge for AI professionals AI specialists and AI engineers.

AI and IoT are inseparable. The entire idea of artificial intelligence is to capture more actionable data from IoT devices.

The Internet of Things is already disrupting various industries impacting human lives in several ways.

Precisely, AI is more about making machines put in intelligent behavior. Whilst, the function of IoT is to make these machines connect. The reciprocal behavior of both these technologies manifests itself in forms that cannot be comprehended.

Thus, AI experts will play a significant role in the unprecedented growth of the IoT era.

Although the disruption of these technologies will not happen overnight, its already indubitably arriving at a much faster pace than expected.

Artificial Intelligence and IoT cannot be ignored anymore!

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Revolutionizing IoT Through AI: Why Theyre Perfect Together - IoT For All

Artificial intelligence has revolutionised every piece of technology it has touched. However, this augmentation for better or worse has also brought up a lot of confusion. With more and more AI application coming up in different fields, specifically in automation like Cognitive Automation, the conditions associated with it give the impression that the technology is artificially intelligent and seems to dilute the real meaning behind it. This poses a more significant problem as what qualifies as a mere application of AI can be called artificial intelligence.

When we talk about automation and AI, there is a lot of buzz around cognitive automation as it uses technology to mimic human behaviour and precisely the reason why some people call it as cognitive automation artificial intelligence.

Artificial Intelligence Vs Cognitive Automation

If one had to define artificial intelligence regarding computing, then it can be defined as the area of computer science that focuses on the creating intelligent machines that work and interact like humans with each other or with living beings. Some activities include speech recognition, learning, among others. When it comes to AI creating intelligent machines that work like humans is what one has to keep in mind from the definition. The creation process depicts the intelligence part of the device.

For example, AI in healthcare has had many applications over the years. Now, if a doctor wants to take the help of an AI, then during a particular procedure, intelligence comes into play when AI suggests which course of action to choose based on its analysis.

Intelligence, especially artificial intelligence, requires a lot of information to carry out its analysis about a process.

On the other hand, cognitive automation mimics quantitative human judgement or augments human intelligence. In short, cognitive automation imitates human thinking. If you look at the technologies in cognitive automation like natural language processing, image processing and contextual analysis all are more profound concepts of perceptions and judgements and are heavily influenced by AI.

If one looks at the cognitive applications, it becomes evident that the automation happens via hardcoded human-generated rules or through dense inputs.

According to Franois Chollet, creator of the neural network library, Keras, Automation is, at best, robustly handling known unknowns over known tasks, which is already incredibly difficult and resource-intensive in the real world whether engineering or data.

Therefore, when it comes to automation, it can only work if it is made aware of the unknowns. Working with the unknown entirely on itself will only result in the failure when it comes to automation. For instance, in the healthcare sector, doctors do take the help of AI for deciding the course of action based on the suggestions made by the intelligent system. However, when it comes to automation, this technology is only here to enhance the doctors practice and not independently run any analysis.

Cognitive automation learns through different unstructured data and connects to creating tags, annotations and other metadata. Cognitive automation tries to find similarities between items to specific processes. It seeks to identify the mentioned items in the process and then searches for similar ones in order to connect them.

To carry out a process by an automation system requires data. And, once enough information has been provided during the automation process, there is no requirement for humans to build an additional model to carry out the analysis further. As the new data set is provided, the automation makes more connections with the old one, which allows the cognitive automation systems to keep learning without any supervision and can continuously adjust to the new information.

Whereas for AI it carries out its analysis after been given a different data set at the expense of a massive amount of information which has been fed to the system. This information/data is more than the required data for cognitive automation.

In the current scenario, when one reads about the cognitive applications, the process and its workings might be similar to artificial intelligence, and thus creating confusion between the two. This happens because ultimately, cognitive automation is an application of artificial intelligence itself, which is just a little less intelligent. Cognitive automation doesnt deal with the unknowns of a process or the real-world problems, and it can only work through them if there is data fed to it in.

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It's 2020 Stop Confusing Cognitive Automation With Artificial Intelligence - Analytics India Magazine

LONDON--(BUSINESS WIRE)--The global artificial intelligence (AI) market in manufacturing industry is expected to post a CAGR of around 31% during the period 2019-2023, according to the latest market research report by Technavio. Request a free sample report

Manufacturing companies are moving toward the implementation of Industry 4.0 standard to intensify automation to achieve higher operational efficiencies. This is increasing the adoption of a greater number of connected devices and technologies such as big data, ML, and IoT, which is resulting in the generation of high volumes of data. This, in turn, is compelling manufacturing firms to adopt AI-based solutions to extract insights from the data to improve the management of operations. Hence, the integration of industrial IoT and big data is crucial in driving the growth of the market.

To learn more about the global trends impacting the future of market research, download a free sample: https://www.technavio.com/talk-to-us?report=IRTNTR32119

As per Technavio, the increasing human-robot collaboration will have a positive impact on the market and contribute to its growth significantly over the forecast period. This research report also analyzes other important trends and market drivers that will affect market growth over 2019-2023.

Global Artificial Intelligence (AI) Market in Manufacturing Industry: Increasing Human-Robot Collaboration

Collaborative robots are designed to work in direct cooperation with humans in a well-defined workspace. They offer better productivity, reduced downtimes, and higher load capacity. Collaborative robots also improve safety in the manufacturing facility and prevent accidents and injury to humans. Moreover, they are affordable, highly adaptable, and are easy to install. Owing to such benefits, many organizations, including SMEs are increasingly adopting collaborative robot technologies. Over the next few years, the demand for collaborative robot technologies is expected to further increase with the development of better sensors and the integration of AI and ML algorithms.

Advances in AI related to intelligent business process and the increasing demand for generative designs will further boost market growth during the forecast period, says a senior analyst at Technavio.

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Global Artificial Intelligence (AI) Market in Manufacturing Industry: Segmentation Analysis

This market report segments the global artificial intelligence market in manufacturing industry by application (predictive maintenance and machine inspection, production planning, quality control, and others) and geography (APAC, Europe, MEA, North America, and South America).

The APAC region led the market in 2018, followed by North America, Europe, South America, and MEA respectively. During the forecast period, the APAC region is expected to maintain its dominance over the market. This is due to the growing adoption of smart technologies by manufacturing facilities in the region.

Technavios sample reports are free of charge and contain multiple sections of the report, such as the market size and forecast, drivers, challenges, trends, and more.

Request a free sample report

Some of the key topics covered in the report include:

Market Landscape

Market Sizing

Five Forces Analysis

Market Segmentation

Customer Landscape

Geographical Segmentation

Market Drivers

Market Challenges

Market Trends

Vendor Landscape

Vendor Analysis

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.

With over 500 specialized analysts, Technavios report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavios comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

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Global Artificial Intelligence (AI) Market in Manufacturing Industry 2019-2023 | 31% CAGR Projection Through 2023 | Technavio - Business Wire

Welcome to the Artificial Intelligence and Games book. This book aims to be the first comprehensive textbook on the application and use of artificial intelligence (AI) in, and for, games. Our hope is that the book will be used by educators and students of graduate or advanced undergraduate courses on game AI as well as game AI practitioners at large.

The book is now available from Springer in digital and printed versions. Click here to access the SpringerLink edition or to buy the hardcopy.

If your institutiondoes not have access to SpringerLink, a pdf version of the book is available here (but please try the link above first).

You can also buy the book from Amazon, though buying directly from Springer may be cheaper.

We are running a summer school on AI and Games, based on the content of the book, in May 2018.

To cite this book you may usethe following bibtex entry:

which yields the following reference (e.g.inChicagostyle):

Yannakakis, Georgios N.,and Julian Togelius. Artificial Intelligence and Games. Springer, 2018.

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Artificial Intelligence and Games A Springer Textbook ...

The future is intelligent: By 2030, artificial intelligence (AI) will add $15.7 trillion to the global GDP, with $6.6 trillion projected to be from increased productivity and $9.1 trillion from consumption effects. Furthermore, augmentation, which allows people and AI to work together to enhance performance, will create $2.9 trillion of business value and 6.2 billion hours of worker productivity globally. In a world that is increasingly characterized by enhanced connectivity and where data is as pervasive as it is valuable, Africa has a unique opportunity to leverage new digital technologies to drive large-scale transformation and competitiveness. Africa cannot and should not be left behind.

There are 10 key enabling technologies that will drive Africas digital economy, including cybersecurity, cloud computing, big data analytics, blockchain, the Internet of Things, 3D printing, biotechnology, robotics, energy storage, and AI. AI in particular presents countless avenues for both the public and private sectors to optimize solutions to the most crucial problems facing the continent today, especially for struggling industries. For example, in health care, AI solutions can help scarce personnel and facilities do more with less by speeding initial processing, triage, diagnosis, and post-care follow up. Furthermore, AI-based pharmacogenomics applications, which focus on the likely response of an individual to therapeutic drugs based on certain genetic markers, can be used to tailor treatments. Considering the genetic diversity found on the African continent, it is highly likely that the application of these technologies in Africa will result in considerable advancement in medical treatment on a global level.

In agriculture, Abdoulaye Banir Diallo, co-founder and chief scientific officer of the AI startup My Intelligent Machines, is working with advanced algorithms and machine learning methods to leverage genomic precision in livestock production models. With genomic precision, it is possible to build intelligent breeding programs that minimize the ecological footprint, address changing consumer demands, and contribute to the well-being of people and animals alike through the selection of good genetic characteristics at an early stage of the livestock production process. These are just a few examples that illustrate the transformative potential of AI technology in Africa.

In a world that is increasingly characterized by enhanced connectivity and where data is as pervasive as it is valuable, Africa has a unique opportunity to leverage new digital technologies to drive large-scale transformation and competitiveness. Africa cannot and should not be left behind.

However, a number of structural challenges undermine rapid adoption and implementation of AI on the continent. Inadequate basic and digital infrastructure seriously erodes efforts to activate AI-powered solutions as it reduces crucial connectivity. (For more on strategies to improve Africas digital infrastructure, see the viewpoint on page 67 of the full report). A lack of flexible and dynamic regulatory systems also frustrates the growth of a digital ecosystem that favors AI technology, especially as tech leaders want to scale across borders. Furthermore, lack of relevant technical skills, particularly for young people, is a growing threat. This skills gap means that those who would have otherwise been at the forefront of building AI are left out, preventing the continent from harnessing the full potential of transformative technologies and industries.

Similarly, the lack of adequate investments in research and development is an important obstacle. Africa must develop innovative financial instruments and public-private partnerships to fund human capital development, including a focus on industrial research and innovation hubs that bridge the gap between higher education institutions and the private sector to ensure the transition of AI products from lab to market.

At the same time, we must be careful that priority sectors drive the AI strategy in Africa with accompanying productsnot the other way around. We believe the health care industry presents by far the most urgent need and promising market opportunity, and, as such, should be put at the top of the list for the continents decisionmakers. A large portion of the African population is still unable to access proper health care, with a low patient ratio of one physician per 5,000 patients, and there is almost no country with a fully integrated health management platform. AI could intervene directly to improve personalized health care and product development. Importantly, the health management platform precedes the leveraging of AI, so we must equally invest in cybersecurity, Big Data, cloud computing, and blockchain.

Artificial intelligence for Africa presents opportunities to put the continent at the forefront of the Fourth Industrial Revolution. Before Africa can lead this transformation, though, there are important steps that must be undertaken. First, the region needs to formulate a comprehensive continental blueprint to guide its AI strategy by involving key Pan-African institutions, academia, and the private and public sectors in its conception.

In addition, these stakeholders must also invest in creating a digital identity platform for all Africans with reliable data banks for AI to be a viable economic option. For this, it is imperative to leverage readily available local talent as a means to promote and democratize AI technology continent-wide. Finally, we must harmonize regulatory policies that encourage ethically built AI systems so as to guarantee a more inclusive economic development for Africa. With these important steps, the next decade for Africa will be intelligent.

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The future is intelligent: Harnessing the potential of artificial intelligence in Africa - Brookings Institution

With the introduction of new export controls on artificial intelligence software last week, the White House appealed to lawmakers, businesses, and European allies to avoid overregulation of artificial intelligence. It also maintained its refusal to participate in a project proposed by the Group of Seven leading economies, which seeks to establish shared principles and regulations on artificial intelligence, as the U.S. prepares to take over the presidency of the organization this year.

The U.S. has rejected working with other G-7 nations on the project, known as the Global Partnership on Artificial Intelligence, maintaining that the plan would be overly restrictive.

Kay Mathiesen is an associate professor of philosophy and religion in the College of Social Sciences and Humanities. Photo by Matthew Modoono/Northeastern University

Kay Mathiesen, an associate professor at Northeastern who focuses on information and computer ethics and justice, contends that the U.S.s refusal to cooperate with other nations on a united plan could come back to hurt its residents.

Advocates of the plan say it would help government leaders remain apprised of the development of the technology. The project, they say, could also help build consensus among the international community on limiting certain uses of artificial intelligence, especially in cases where its found to be controlling citizens or violating their privacy and autonomy.

U.S. leaders, including deputy chief technology officer Lynne Parker, counter that the proposal appears overly bureaucratic and could hinder the development of artificial intelligence at U.S. tech companies.

But Mathiesen says that many companies are already ahead of the curve in considering or implementing oversight mechanisms to guide the ethical development of their products. She says that its important to rein in the potentially harmful effects of artificial intelligence to ensure that the benefits of the technology are not overridden by the cost.

The idea that we should just not regulate at all or not even think about this, because maybe then we might limit ourselves, I think thats a pretty simplistic view, says Mathiesen, a professor of philosophy who studies political philosophy and ethics. Its not like the G-7 is going to have the power to all of a sudden impose regulations on U.S. industry. So that argument that merely by joining this [group] and beginning to think these things through, and do research on this, and develop [policy] recommendationsthat that by itself is going to put us behind on artificial intelligence doesnt hold a lot of water.

Mathiesen suggests that failing to work with other countries in addressing privacy issues stemming from the unchecked spread of artificial intelligence productssuch as facial recognitioncould result in consumer backlash, and thereby slow down the development of artificial intelligence in the U.S.

The technology is advancing incredibly rapidly and we want to make sure that were thinking ahead, and were building at the beginning protections for consumers before these things come out and its too late and we have to try to fix problems that we couldve prevented, she says.

The plan for the Global Partnership on Artificial Intelligence, which was introduced in December 2018, is to ensure that artificial intelligence projects are designed responsibly and transparently, in a way that prioritizes human values, such as privacy. The initiative received a major boost from Canada, which held the G-7s rotating presidency at the time, and was kept alive by France the following year. The U.S. will take over the presidency of the organization this year.

In addition to Canada and France, the other G-7 countries, including Germany, Italy, Japan, and the U.K., are on board with the project. The European Union, India, and New Zealand have also expressed interest. Mathiesen says that while she understands the concerns of some U.S. government officials about being out-competed, its important for the U.S. to be a participating member in this effort, especially while the technology is still in its nascent stages.

In a way, its better that the U.S. has buy-in at the beginning and is at the table to make these arguments about how do we balance concerns about things like privacy, security, and possible harm that could be produced by artificial intelligence? How do we balance that with also wanting to enable companies and inventors to create new things with artificial intelligence that can be economically and socially beneficial? she says.

Mathiesen suggested that failing to engage in these conversations with the wider international community could leave the U.S. trailing behind.

I think that the American citizens are going to suffer for that, just like they do now with the lack of data privacy, she says.

In conjunction with global professional services company Accenture, researchers at Northeasterns Ethics Institute last year produced a report that provided organizations a framework for creating ethics committees to help guide the development of smart machines.

For media inquiries, please contact Marirose Sartoretto at m.sartoretto@northeastern.edu or 617-373-5718.

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The G7 wants to regulate artificial intelligence. Should the US get on board? - News@Northeastern