Tommie Experts taps into the knowledge of St. Thomas faculty and staff to help us better understand topical events, trends and the world in general.

Last month, School of Engineering Dean Don Weinkauf appointed Manjeet Rege, PhD, as the director for the Center for Applied Artificial Intelligence.

Rege is a faculty member, author, mentor, AI expert, thought leader and a frequent public speaker on big data, machine learning and AI technologies. The Newsroom caught up with him to ask about the centers launch in response to a growing need to educate ethically around AI.

Were partnering with industry in a number of ways. One way is in our data science curriculum. There are electives; some students take a regular course, while others take a data science capstone project. Its optional. Students who opt for that through partnership with the industry, companies in the Twin Cities interested in embarking on an AI journey can have several business use cases that they want to try AI out with. In an enterprise, you typically have to seek funding, convince a lot of people; in this case, well find a student, or a team, who will be working on that industry-sponsored project. Its a win-win for all. The project will be supervised by faculty. The company gets access to emerging AI talent, gets to try out their business use case and the students end up getting an opportunity working on a real-world project.

Secondly, a number of companies are looking to hire talent in machine learning and AI. This is a good way for companies to access good talent. We can build relationships, sending students for internships, or even students who work on these capstone projects become important in terms of hiring.

There are also a number of professional development offerings well come out with. We offer a mini masters program in big data and AI. The local companies can come and attend an executive seminar for a week on different aspects of AI. Well be offering two- or three-day workshops on hands-on AI, for someone within a company who would like to become an AI practitioner. If they are interested in getting in-depth knowledge, they can go through our curriculum.

We also have a speaker series in partnership with SAS.

In May well be hosting a data science day, a keynote speaker, and a panel of judges to review projects the data science students are working on (six of which are part of the SAS Global Student Symposium). Theyll get to showcase the work theyve done. That panel of judges will be from local companies.

Everybody is now becoming aware that AI is ubiquitous, around us and here. The ship has already left the dock, so to speak, in terms of AI being around us. The best way to succeed at the enterprise level is to embrace this and make it a business enabler. Its important for enterprises to transform themselves into an AI-first company. Think about Google. It first defined itself as a search company. Then a mobile company. Now, its an AI-first company. That is what keeps you ahead, always.

Being aware of the problems that may arise is so important. For us to address AI biases, we have to understand how AI works. Through these multiple offerings were hoping we can create knowledge about AI. Once we have that we can address the issue of AI bias.

For example, Microsoft did an experiment where it had AI go out on the web, read the literature and learn a lot of analogies. When you went in and asked that AI questions based on, say, what man is to a woman, father is to what? Mother. Perfect. What man is to computer programmer as woman is to what? Homemaker. Thats unfortunate. AI is learning the stereotypes that exist in the literature it was learned on.

There have been hiring tools that have gender bias. Facial recognition tools that work better for lighter skin colors than darker skin colors. Bank loan programs with biases for certain demographics. There is a lot of effort in the AI community to minimize these. Humans have bias, but when a computer does it you expect perfection. An AI system learning is like a child learning; when that AI system learned about different things from the web and different relationships between man and woman, because these stereotypes existed already in the data, the computer just learned from it. Ultimately an AI system is for a human; whenever it gives you certain output, we need to be aware and go back and nudge it in the right direction.

Link:

Tommie Experts: Ethically Educating on Artificial Intelligence at St. Thomas - University of St. Thomas Newsroom

2019 has seen artificial intelligence and machine learning take centre stage for many industries, with companies increasingly looking to harness the benefits of the technology for a wide range of use cases. With its advances, ethical implications and impact on humans likely to dominate conversations in the technology sector for years to come, how will AI continue to develop over the next 12 months?

Weve asked experts from a range of organisations within the AI sphere to give their predictions for 2020.

In both the private and public sectors, organisations are recognising the need to develop strategies to mitigate bias in AI. With issues such as amplified prejudices in predictive crime mapping, organisations must build in checks in both AI technology itself and their people processes. One of the most effective ways to do this is to ensure data samples are robust enough to minimise subjectivity and yield trustworthy insights. Data collection cannot be too selective and should be reflective of reality, not historical biases.

In addition, teams responsible for identifying business cases and creating and deploying machine learning models should represent a rich blend of backgrounds, views, and characteristics. Organisations should also test machines for biases, train AI models to identify bias, and consider appointing an HR or ethics specialist to collaborate with data scientists, thereby ensuring cultural values are being reflected in AI projects.

Zachary Jarvinen, Head of Technology Strategy, AI and Analytics, OpenText

A big trend for social media this year has been the rise of deepfakes and were only likely to see this increase in the year ahead. These are manipulated videos that are made to look real, but are actually inaccurate representations powered by sophisticated AI. This technology has implications for past political Facebook posts. I believe we will start to see threat actors use deepfakes as a tactic for corporate cyberattacks, in a similar way to how phishing attacks operate.

Cyber crooks will see this as a money-making opportunity, as they can cause serious harm on unsuspecting employees. This means it will be vital for organisations to keep validation technology up-to-date. The same tools that people use to create deepfakes will be the ones used to detect them, so we may see an arms race for who can use the technology first.

Jesper Frederiksen, VP and GM EMEA, Okta

When considering high-volume, fast turnaround hiring efforts, its often impossible to keep every candidate in the loop. Enter highly sophisticated artificial intelligence tools, such as chatbots. More companies are now using AI programs to inform candidates quickly and efficiently on where they stand in the process, help them navigate career sites, schedule interviews and give advice. This is significantly transforming the candidate experience, enhancing engagement and elevating overall satisfaction.

Chatbots are also increasingly becoming a tool for employees who wish to apply for new roles within their organisation. Instead of trying to work up the nerve to ask HR or their boss about new opportunities, employees can interact with a chatbot that can offer details about open jobs, give skills assessments and offer career guidance.

Whats more, some companies are offering day in the life virtual simulations that allow candidates to see what a role would entail, which can either enhance interest or help candidates self-select out of the process. It also helps employers understand if the candidate would be a good fit, based on their behavior during the simulation. In Korn Ferrys global survey of HR professionals, 78 percent say that in the coming year, it will be vital to provide candidates with these day in the life type experiences.

Byrne Mulrooney, Chief Executive Officer, Korn Ferry RPO, Professional Search and Korn Ferry Digital

Get the Verdict morning email

Despite fears that it will replace human employees, in 2020 AI and machine learning will increasingly be used to aid and augment them. For instance, customer service workers need to be certain they are giving customers the right advice. AI can analyse complex customer queries with high numbers of variables, then present solutions to the employee speeding up the process and increasing employee confidence.

Lufthansa for one is already using this method, and with a faster, more accurate and ultimately more satisfying customer experience acting as a significant differentiator more will follow. Over the next three years this trend will keep accelerating, as businesses from banks to manufacturers use AI to support their employees decisions and outperform the competition.

Felix Gerdes, Director of Digital Innovation Services at Insight UK

In 2020 were going to see increased public demand for the demystification and democratisation of AI. There is a growing level of interest and people are quite rightly not happy to sit back and accept that a robot or programme makes the decisions it does because it does or that its simply too complicated. They want to understand how varying AI works in principle, they want to have more of a role in determining how AI should engage in their lives so that they dont feel powerless in the face of this new technology.

Companies need to be ready for this shift, and to welcome it. Increasing public understanding of AI, and actively seeking to hear peoples hopes and concerns is the only way forward to ensure that the role of AI is both seen as a force for good for everyone in our society and as a result able to realise the opportunity ahead historically not something that tech industry as a whole have been good at, we need to change.

Teg Dosanjh, Director of Connected Living for Samsung UK and Ireland

As the next decade of the transforming transportation industry unfolds, investment in autonomous vehicle development will continue to grow dramatically, especially in the datacenter and AI infrastructure for training and validation. Well see a significant ramp in autonomous driving pilot programs as part of this continued investment. Some of these will include removal of the on-board safety driver. Autonomous driving technology will be applied to a wider array of industries, such as trucking and delivery, moving goods instead of people.

Production vehicles will start to incorporate the hardware necessary for self-driving, such as centralized onboard AI compute and advanced sensor suites. These new features will help power Level 2+ AI assisted driving and lay the foundation for higher levels of autonomy. Regulatory agencies will also begin to leverage new technologies to evaluate autonomous driving capability, in particular, hardware-in-the-loop simulation for accurate and scalable validation. The progress in AV development underway now and for the next few years will be instrumental to the coming era of safer, more efficient transportation.

Danny Shapiro, Senior Director of Automotive, NVIDIA

As AI tools become easier to use, AI use cases proliferate, and AI projects are deployed, cross-functional teams are being pulled into AI projects. Data literacy will be required from employees outside traditional data teamsin fact, Gartner expects that 80% of organisations will start to roll out internal data literacy initiatives to upskill their workforce by 2020.

But training is an ongoing endeavor, and to succeed in implementing AI and ML, companies need to take a more holistic approach toward retraining their entire workforces. This may be the most difficult, but most rewarding, process for many organisations to undertake. The opportunity for teams to plug into a broader community on a regular basis to see a wide cross-section of successful AI implementations and solutions is also critical.

Retraining also means rethinking diversity. Reinforcing and expanding on how important diversity is to detecting fairness and bias issues, diversity becomes even more critical for organisations looking to successfully implement truly useful AI models and related technologies. As we expect most AI projects to augment human tasks, incorporating the human element in a broad, inclusive manner becomes a key factor for widespread acceptance and success.

Roger Magoulas, VP of Radar at OReilly

The hottest trend in the industry right now is in Natural Language Processing (NLP). Over the past year, a new method called BERT (Bidirectional Encoder Representations from Transformers) has been developed for designing neural networks that work with text. Now, we suddenly have models that will understand the semantic meaning of whats in text, going beyond the basics. This creates a lot more opportunity for deep learning to be used more widely.

Almost every organisation has a need to read and understand text and spoken word whether it is dealing with customer enquiries in the contact centre, assessing social media sentiment in the marketing department or even deciphering legal contracts or invoices. Having a model that can learn from examples and build out its vocabulary to include local colloquialisms and turns of phrase is extremely useful to a much wider range of organisations than image processing alone.

Bjrn Brinne, Chief AI Officer at Peltarion

Voice assistants have established themselves as common place in our personal lives. But 2020 will see an increasing amount of businesses turning to them to improve and personalise the customer experience.

This is because, advances in AI-driven technology and natural language processing are enabling voice interactions to be translated into data. This data can be structured so that conversations can be analysed for insights.

Next year, organisations will likely begin to embrace conversational analytics to improve their chatbots and voice applications. This will ultimately result in better data-driven decisions and improved business performance.

Alberto Pan, Chief Technical Officer, Denodo

Organisations are already drowning in data, but the flood gates are about to open even wider. IDC predicts that the worlds data will grow to 175 zettabytes over the next five years. With this explosive growth comes increased complexity, making data harder than ever to manage. For many organisations already struggling, the pressure is on.

Yet the market will adjust. Over the next few years, organisations will exploit machine learning and greater automation to tackle the data deluge.

Machine learning applications are constantly improving when it comes to making predictions and taking actions based on historical trends and patterns. With its number-crunching capabilities, machine learning is the perfect solution for data management. Well soon see it accurately predicting outages and, with time, it will be able to automate the resolution of capacity challenges. It could do this, for example, by automatically purchasing cloud storage or re-allocating volumes when it detects a workload nearing capacity.

At the same time, with recent advances in technology we should also expect to see data becoming more intelligent, self-managing and self-protecting. Well see a new kind of automation where data is hardwired with a type of digital DNA. This data DNA will not only identify the data but will also program it with instructions and policies.

Adding intelligence to data will allow it to understand where it can reside, who can access it, what actions are compliant and even when to delete itself. These processes can then be carried out independently, with data acting like living cells in a human body, carrying out their hardcoded instructions for the good of the business.

However, with IT increasingly able to manage itself, and data management complexities resolved, what is left for the data leaders of the business? Theyll be freed from the low-value, repetitive tasks of data management and will have more time for decision-making and innovation. In this respect AI will become an invaluable tool, flagging issues experts may not have considered and giving them options, unmatched visibility and insight into their operations.

Jasmit Sagoo, Senior Director, Head of Technology UK&I at Veritas Technologies

2020 will be the year research & investment in ethics and bias in AI significantly increases. Today, business insights in enterprises are generated by AI and machine learning algorithms. However, due to these algorithms being built using models and data bases, bias can creep in from those that train the AI. This results in gender or racial bias be it for mortgage applications or forecasting health problems. With increased awareness of bias in data, business leaders will demand to know how AI reaches the recommendations it does to avoid making biased decisions as a business in the future.

Ashvin Kamaraju, CTO for Cloud Protection and Licensing activity atThales

2020 will be the year of health data. Everyone is agreed that smarter use of health data is essential to providing better patient care meaning treatment that is more targeted or is more cost effective. However, navigating through the thicket of consents and rules as well as the ethical considerations has caused a delay to advancement of the use of patient data.

There are now several different directions of travel emerging which all present exciting opportunities for patients, for health providers including the NHS, for Digital Health companies and for pharmaceutical companies.

Marcus Vass, Partner, Osborne Clarke

Artificial intelligence isnt just something debated by techies or sci-fi writers anymore its increasingly creeping into our collective cultural consciousness. But theres a lot of emphasis on the negative. While those big picture questions around ethics cannot and should not be ignored, in the near-term we wont be dealing with the super-AI you see in the movies.

Im excited by the possibilities well see AI open up in the next couple of years and the societal challenges it will inevitably help us to overcome. And its happening already. One of the main applications for AI right now is driving operational efficiencies and that may not sound very exciting, but its actually where the technology can have the biggest impact. If we can use AI to synchronise traffic lights to impact traffic flow and reduce the amount of time cars spend idling, that doesnt just make inner city travel less of a headache for drivers it can have a tangible impact on emissions. Thats just one example. In the next few years, well see AI applied in new, creative ways to solve the biggest problems were facing as a species right now from climate change to mass urbanisation.

Dr Anya Rumyantseva, Data Scientist at Hitachi Vantara

Businesses are investing more in AI each year, as they look to use the technology to personalize customer experiences, reduce human bias and automate tasks. Yet for most organizations AI hasnt yet reached its full potential, as data is locked up in siloed systems and applications.

In 2020, well see organizations unlock their data using APIs, enabling them to uncover greater insights and deliver more business value. If AI is the brain, APIs and integration are the nervous system that help AI really create value in a complex, real-time context.

Ian Fairclough, VP of Services, MuleSoft

2020 is going to be a tipping point, when algorithmic decision making AI will become more mainstream. This brings both opportunities and challenges, particularly around the explainability of AI. We currently have many blackbox models where we dont know how its coming to decisions. Bad guys can leverage this and manipulate these decisions.

Using machine identities, they will be able to infiltrate the data streams that feed into an AI models and manipulate them. If companies are unable to explain and see the decision making behind their AI this could go unquestioned, changing the outcomes. This could have wide reaching impacts in everything from predictive policing to financial forecasting and market decision making.

Kevin Bocek, Vice President, Security Strategy & Threat Intelligence at Venafi

Until now, robotic process automation (RPA) and artificial intelligence (AI) have been perceived as two separate things: RPA being task oriented, without intelligence built in. However, as we move into 2020, AI and machine learning (ML) will become an intrinsic part of RPA infused throughout analytics, process mining and discovery. AI will offer various functions like natural language processing (NLP) and language skills, and RPA platforms will need to be ready to accept those AI skill sets. More broadly, there will be greater adoption of RPA across industries to increase productivity and lower operating costs. Today we have over 1.7 million bots in operation with customers around the world and this number is growing rapidly. Consequently, training in all business functions will need to evolve, so that employees know how to use automation processes and understand how to leverage RPA, to focus on the more creative aspects of their job.

RPA is set to see adoption in all industries very quickly, across all job roles, from developers and business analysts, to programme and project managers, and across all verticals, including IT, BPO, HR, Education, Insurance and Banking. To facilitate continuous learning, companies must give employees the time and resources needed to upskill as job roles evolve, through methods such as micro-learning and just in time training. In the UK, companies are reporting that highly skilled AI professionals, currently, are hard to find and expensive to hire, driving up the cost of adoption and slowing technological advancement. Organisations that make a conscious decision to use automation in a way that enhances employees skills and complements their working style will significantly increase the performance benefit they see from augmentation.

James Dening, Vice President for Europe at Automation Anywhere

Read more: Artificial intelligence to create 133 million jobs globally: Report

Follow this link:

Artificial intelligence predictions for 2020: 16 experts have their say - Verdict

DUBLIN--(BUSINESS WIRE)--The "Innovations in Artificial Intelligence-, Cloud-, and IoT-based Security" report has been added to ResearchAndMarkets.com's offering.

This Cyber Security TechVision Opportunity Engine (TOE) provides a snapshot on emerging cyber security solutions powered by artificial intelligence, cloud, and IoT innovations that help companies protect from threats, data breaches, phishing, other advanced and targeted attacks. They also defend against and prevent modern attacks residing within cloud, endpoints, and various network layers.

Cyber Security TechVision Opportunity Engine's mission is to investigate new and emerging developments that aim to protect the network infrastructure and the resources operating in the network. The TOE offers strategic insights that would help identify new business opportunities and enhance technology portfolio decisions by assessing new developments and product launches in: anti-spam, anti-virus, phishing, identity management, disaster recovery, firewalls, virtual private networks, end-point security, content filtering,

Web application security, authentication and access control, intrusion prevention and detection systems, encryption algorithms, cryptographic techniques, and pattern recognition systems for network security.

Highlights of this service include technology roadmapping of network security technologies; IP portfolio analysis; information on funding and investment opportunities; evaluation of commercial opportunities from technology developments; technology assessment; analysis of technology accelerators and challenges and many more.

Key Topics Covered:

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/n3ivvh

View post:

Innovations in Artificial Intelligence-, Cloud-, and IoT-based Security, 2019 Research Report - ResearchAndMarkets.com - Business Wire

Artificial Intelligence is being accused of fueling inequality and climate change as revealed by a new report.

Recently, a paper was published by the AI Now Institute with a title AI Now 2019 Report and it is highlighting the societal impacts of artificial intelligence and is also putting in front some recommendations for the tech industry and policymakers.

The artificial intelligence is being controlled by the people who already have power and is promoting inequality, and disempowering people who lack power.

According to the claims by AI Now, the artificial intelligence industry is promoting the mistreatment and discrimination of workers as the tech companies are moving more towards facial recognition technologies and ignoring the facts that these energy-running A.I. systems are the reason behind the increase of carbon dioxide in the environment.

According to the co-founder of AI Now Kate Crawford, her organization is concerned about the effects of the recognition technology that is promoting to determine the personality or emotional state of a person via their facial expression and this type of technology is being used by vet job applicants, to track students and to gather data on the emotional states of shoppers inside the stores. So the organization is asking for a ban on this technology before it can be used in furthermore critical decisions like hiring.

In this report AI NOW 2019, the researchers also recommend Senator Bernie Sanders to make a ban on police facial recognition as a part of his presidential campaign to help stop the misuse before its too late.

Another major concern raised via this report is the impact of power-hungry artificial intelligence programs on the environment and AI Now also displayed a report of a group of University of Massachusetts, Amherst which determined that the energy consumed by A.I. training model produced 600,000 pounds of carbon dioxide emissions and due to this reason the only solution provided by the researchers of AI was to put completely end the usages of carbon dioxide emitting technology to stop the increase of climate change.

This report also highlights the issue of Biometric Information Privacy as it can be used to track a person easily so the recommendations also include the enabling of the Biometric Information Privacy act so that legal action can be taken against the collection of biometric information by a person or company without consent.

Another issue raised in this report was the lack of diversity in the tech industry, as the tech industry is slowly squeezing out the involvement of human employees which means the tech works cant speak about the ethical concerns regarding their work to A.I. enabled systems as most of the department decisions are now being down by the A.I. enabled systems which are inaccessible to the workers and the public.

According to the report, three municipalities in the United States have already banned the use of facial recognition from the government and the San Francisco, Oakland, and Somerville, Massachusetts have stalled its use so far.

KENGKAT via Getty Images

Read next: The Emerging Jobs to look out for in 2020 According to LinkedIn

The rest is here:

Artificial Intelligence might be a factor behind the Climate Change - Digital Information World