Commentary

Photo by Michael Langan

ByOren Etzioni & Carissa Schoenick

Editors Note: This Commentary is part of a special report exploring game-changing trends and innovations that have the potential to shake up the schoolhouse.Read the full report: 10 Big Ideas in Education.

Artificial intelligence is a rapidly emerging technology that has the potential to change our everyday lives with a scope and speed that humankind has never experienced before. Some well-known technology leaders such as Tesla architect Elon Musk consider AI a potential threat to humanity and have pushed for its regulation "before it's too late"an alarmist statement that confuses AI science with science fiction. What is the reality behind these concerns, and how can educators best prepare for a future with artificial intelligence as an inevitable part of our lives?

General, widespread legislative regulation of AI is not going to be the right way to prepare our society for these changes. The AI field is already humming with a wide variety of new research at an international scale, such that blindly constraining AI research in its early days in the United States would only serve to put us behind the global curve in developing the most important technology of the future. It is also worth noting that there are many applications of AI currently under development that have huge potential benefits for humanity in the fields of medicine, security, finance, and personal services; we would risk a high human and economic cost by slowing or stopping research in those areas if we hastily impose premature, overbearing, and poorly understood constraints.

Oren Etzioni & Carissa Schoenick are CEO and senior program manager at the Allen Institute for Artificial Intelligence, respectively.

Based in Seattle, Etzioni is a professor of computer science at the University of Washington; Schoenick was previously a program manager for Amazon Web Services and for the computational knowledge project WolframAlpha.

The most impactful way to shape the future of AI is not going to be through the regulation of research, but rather through understanding and correctly controlling the tangible impacts of AI on our lives. For example, it is our belief that AI should not be weaponized, and that humans should always have the ultimate "off switch." Beyond these obvious limitations, there are three rules we propose for AI that can be meaningfully applied now to mitigate possible future harm.

An AI system:

1) Must always respect the same laws that apply to its creators and operators;

2) Must always disclose that it is not human whenever it interacts with another entity;

3) Should never retain or share confidential information without explicit approval from the source.

These rules are a strong practical starting point, but to successfully navigate the new world AI will bring about in the coming decades, we're going to need to ensure that our children are learning the skills required both to make sense of this new human-machine dynamic and to control it in the right ways. All students today should be taught basic computer literacy and the fundamentals behind how an AI works, as they will need to be comfortable with learning and incorporating rapidly emerging new technologies into their lives and occupations as they are developed.

We will need our future scientists and engineers to be keenly aware that an AI system can only be as good as the data it is given to work with, and that to avoid dangerous bias or incorrect actions, we need to cultivate the right inputs to these systems that fairly cover all possible perspectives and variables. We will need policymakers who can successfully apply the rules suggested above as well as define the new ones we will need as AI continues to proliferate into the various aspects of our lives.

New and different opportunities and values will likely emerge for humans in the economy that AI creates. As AI makes more resources more widely available, we will find less meaning in material wealth and more value in the activities that are uniquely human. This means that occupations with creative and expressive qualities, such as chefs, tailors, organic farmers, musicians, and artists of all types will become more important in an age in which a real human connection is increasingly precious. Roles that directly affect human development and well-being, such as teaching, nursing, and caregiving, will be especially crucial and should be uplifted as excellent options for people whose vocations are otherwise replaced by AI systems. No AI can hope to match a human for true compassion and empathy, qualities that we should be taking extra care to cultivate in our children to prepare them to inherit a world where these characteristics will be more important than ever.

Background

By Benjamin Herold

What will the rise of artificial intelligence mean for K-12 education?

First, AI and related technologies are reshaping the economy. Some jobs are being eliminated, many others are being changed, and entirely new fields of work are opening up. Those changes are likely to have big implications for the job market in 2030, when today's 6th graders are set to hit their prime working years. But the nation's top economists and technologists are sharply divided about whether AI will be a job killer or creator, presenting a big challenge for the educators and policymakers who must prepare today's students to thrive in a very uncertain tomorrow.

Second, artificial intelligence is changing what it means to be an engaged citizen. K-12 education has never been just about preparing young people for jobs; it's also about making sure they're able to weigh arguments and evidence, synthesize information, and take part in the civic lives of their communities and country. But as algorithms, artificial intelligence, and automated decisionmaking systems are being woven into nearly every aspect of our lives, from loan applications to dating to criminal sentencing, new questions and policy debates and ethical quandaries are emerging. Schools are now faced with having to figure out how to teach students to think critically about the role these technologies are playing in our society and how to use them in smart, ethical ways. Plus, in the age of AI, students will likely have to develop a new communication skill: the ability to talk effectively to intelligent machines. Some economists say that skill could be the difference between success and failure in the workplace of the future.

And third, artificial intelligence could play a powerful role in the push to provide more personalized instruction for all studentsand in the process change the teaching profession itself. Intelligent tutoring systems are making inroads in the classroom. New educational software and technology platforms use algorithms to recommend content and lessons for individual students, sometimes pushing teachers away from the front of the classroom and into the role of "coach" or "facilitator." And schools are being flooded with data about their students, information that educators and administrators alike are increasingly expected to use to make real-time decisions and adjustments in the course of their day-to-day work.

Some educators see the rising role of AI as a threat to their existence and a danger to student-data privacy. Others take a more positive view, seeing it as having the potential to free them from mundane tasks like lecturing and grading, creating rich opportunities for continuous improvement, and opening the doors for more meaningful trial-and-error learning by students.

Whatever the perspective, there is one thing most everyone seems to agree on: Now is the time for the K-12 field to start wrestling with the promises and perils of AI.

Vol. 37, Issue 16, Pages 28-29

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Artificial Intelligence: What Educators Need to Know ...

As an expert, Im often asked: what will this year bring? I dont have a glass ball to look into the future, or an artificial intelligence (AI)-based system for these kinds of predictions, but there are some interesting trends I certainly want to share.

I will not discuss the growth figures of AI use cases, or whether those not using AI will limp along behind, or whether the AI bubble will burst and a new AI winter will come. Much progress has been made, but not enough to deflect the next hurdle: and that is how to gain knowledge about your business domain with the help of AI.

So, what will AI bring us in the near future? Let me discuss three important topics:

AI is already starting to transform how organizations do business, manage their customer relationships, and stimulate the ideas and creativity that fuel ground-breaking innovation. (Capgemini)

Three years ago, good use cases for machine learning were hard to find. Now, success stories are everywhere. Machine learning, deep learning, neural networks, and all the other variants are now plentiful. So, whatever will happen this year, machine learning is here to stay and, it will become even more successful as more businesses start to use AI for their daily activities.

All these AI algorithms now constitute an integral part of many data-driven tools. For data analysts, using AI is just a click away. But does this imply that AI is used correctly? Im afraid not, because:

But theres more to business processes than task execution. How can we determine if our AI is really an improvement over human-based actions? This is still an open discussion.

Currently, we see machine learning being used in very narrow applications, to make process steps more efficient or to alleviate tedious jobs. But how AI will contribute to a meaningful return on investment has also been a big question, both last year and in 2020.

AI ethics isnt just a feel-good add-on a want but not a need. AI has been called one of the great human rights challenges of the 21st century. (Khari Johnson)

Last year, discussions about the ethics of AI really took off. Though mainly academic, the discussion now focuses not only on the (im)moral consequences of AI, for instance discrimination, job loss, inequality, and so on. The focus now is on values. Is there a thing like AI for good? Do we as a society really want to give decisive powers to machines? And are those machine fair and open? And what about checks and balances?

These discussions do not focus on AI alone. They also concern the use of big data. Smart cities, facial recognition, fraud detection these are all areas where privacy and expedience are to be discussed and assessed. This will require the evaluation of the ethical side from the beginning of the project. Will the ethics of AI be a burdensome duty or a real competitive advantage? I dont know yet.

We will see the rise of ethical frameworks. Just like compliance frameworks for accounting, these frameworks will offer ways of assessing the ethical implications of AI. Like any framework, they are no excuse not to think independently and systematically about AI. Frameworks dont guarantee a good outcome. And the discussion will arise on how to use these frameworks in a business context.

My recent three part blog on ethics (part 1, part 2, part 3) describes an approach to implementing ethics for AI in products, services, and businesses.

Deep learning has instead given us machines with truly impressive abilities but no intelligence. The difference is profound and lies in the absence of a model of reality. (Judea Pearl)

Machine learning, including deep learning and neural networks, is highly successful. These methods are all very good in extracting information from data. Yes, Im aware of the numerous mistakes machine learning makes, and about how machine learning, mostly image recognition, can be fooled. We must learn from these mistakes by improving the algorithms and learning processes. But AI of far more than machine learning alone. Cognitive Computing, Symbolic AI and Contextual Reasoning are also AI. We need to re-evaluate the use of these other AI- techniques for our applications.

This year, well continue to open the black box of machine learning. The algorithms will, through interpretable machine learning, provide insights into how they reached their decisions. But AI in a business context will not be able to evaluate the correctness and fairness of the decisions.

Machine learning is good at extracting information from data, but its lousy at extracting knowledge from information. For data to become information, it must be contextualized, categorized, calculated, and condensed. Information is key for knowledge. Knowledge is closely linked to doing and implies know-how and understanding. This raises the decades-old philosophical question of AI: Do AI systems really understand what they are doing?

Without visiting John Searles Chinese Room again, I truly think that the next step in AI can only be taken once we incorporate some level of knowledge or understanding of AI. In order to do that, well have to take another step toward human-like AI. For example, by using symbolic AI (or classical AI). This is the branch of AI research that concerns itself with attempting to explicitly represent human knowledge in a declarative form (i.e., facts and rules). Combining these older techniques with neural networks in a hybrid form, will take AI even further. This means that causation, knowledge representation, and so on are key factors necessary to take AI to the next level a next level that will be even more exciting than the achievements AI has reached this year.

For more information on this connect with Reinoud Kaasschieter.

Originally posted here:
What will artificial intelligence bring in 2020?

By 2024, artificial intelligence (AI) and emerging technologies such as virtual personal assistants and chatbots will replace almost 69 per cent of the manager's workload, predicts research and advisory firm Gartner, Inc.

Such technologies are rapidly making headway into the workplace, Gartner said.

"The role of manager will see a complete overhaul in the next four years," said Helen Poitevin, research vice- president at Gartner, in a statement.

"Currently, managers often need to spend time filling in forms, updating information and approving workflows. By using AI to automate these tasks, they can spend less time managing transactions and can invest more time on learning, performance management and goal setting," she said.

AI and emerging technologies will undeniably change the role of the manager and will allow employees to extend their degree of responsibility and influence, without taking on management tasks, Gartner said.

Application leaders focused on innovation and AI are now accountable for improving worker experience, developing worker skills and building organisational competency in responsible use of AI, it was noted.

"Application leaders will need to support a gradual transition to increased automation of management tasks as this functionality becomes increasingly available across more enterprise applications, said Poitevin.

Nearly 75 per cent of heads of recruiting reported that talent shortages will have a major effect on their organisations, according to Gartner.

Enterprises have been experiencing critical talent shortage for several years.

Organisations need to consider people with disabilities, an untapped pool of critically skilled talent.

Today, AI and other emerging technologies are making work more accessible for employees with disabilities.

Gartner estimates that organisations actively employing people with disabilities have 89 per cent higher retention rates, a 72 per cent increase in employee productivity and a 29 per cent increase in profitability.

In addition, Gartner said that by 2023, the number of people with disabilities employed will triple, due to AI and emerging technologies reducing barriers to access.

"Some organisations are successfully using AI to make work accessible for those with special needs," said Poitevin.

"Restaurants are piloting AI robotics technology that enables paralysed employees to control robotic waiters remotely. With technologies like braille-readers and virtual reality, organisations are more open to opportunities to employ a diverse workforce," she said.

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