Technology is creating ever-changing expectations for people, and Gartner's top predictions for 2020 reflect these new challenges. The predictions were revealed at the Gartner IT Symposium/Xpo 2019 in Orlando, which runs through October 24. More than 9,000 IT leaders and CIO's are in attendance at the conference. "Technology is changing the notion of what it means to be human," said Daryl Plummer, distinguished vice president and Gartner Fellow. "As workers and citizens see technology as an enhancement of their abilities, the human condition changes as well. CIOs in end-user organizations must understand the effects of the change and reset expectations for what technology means."

While many chatbots didn't live up to the hype, industries like fintech, healthcare, and retail are quietly adopting the technology to free up busy professionals' time and offer guided, personalized experiences to consumers. In 2016, chatbots were all the rage. That year, Facebook made the Messenger bot platform the centerpiece of its F8 developer conference. Microsoft's Satya Nadella referred to chat as the "third run-time" -- an indispensable piece of operating a platform, second only to the operating system and the web browser. Mentions of chatbots in earnings calls and press releases skyrocketed, and for many, it seemed that chatbots might be the next big disruptive technology. Thousands of companies commissioned their own chatbots in anticipation. In the end, though, the expected paradigm shift didn't happen. There are many reasons why chat didn't take off in 2016. For one, consumers found that many of the tasks the first chatbots were built to perform -- like relaying the news or finding a recipe -- took more time when a bot was involved. Another problem was that bots regularly needed human assistance to understand commands. Even Facebook's much-hyped personal assistant, M, closed down shortly after it was revealed that human handlers were responsible for some 70% of the bot's responses. But while many chatbots didn't meet users' high expectations, they haven't entirely fallen short. Today, the bots are still being used across industries like fintech, healthcare, sales and CRM, retail, and even law -- and they're having important, though quiet, effects. The important chatbots of 2019 aren't all-knowing virtual butlers; they're highly targeted applications of conversational technology. While they may seem less flashy, these bots are advancing their technology and making a demonstrable impact on their industries.

In Hong Kong, there are over two and a half thousand startups, employing nearly 10,000 people. Companies like Zegal are tapping into this deep talent pool and quickly changing the game for businesses that might have balked at complex legal documentation previously. "Historically, legal has been an intimidating topic area for individual companies, especially small and medium enterprises and law firms," says Tai Hung-Chou, CTO of Zegal. "We provide one place where clients and lawyers can work to get contracts drafted and executed, all online. In the future, with advanced natural language processing and artificial intelligence tools, we will [be able to] allow access to a vast array of legal precedents that can be injected during the drafting process."

Justice Sharad Arvind Bobde, who will be succeeding Chief Justice of India Ranjan Gogoi has proposed the usage of high-end technology including Artificial Intelligence in courts. Justice Bobde who will be the 47th Chief Justice of India has asserted that there may be a need for some minor changes in the justice system of the country by the inclusion of the use of technology such as artificial intelligence. "Justice delivery system is good, it might require some minor changes, including the use of technology like artificial intelligence. It's a good system, you need to use some other things," Justice Bobde told ANI. He said the justice delivery system is good, but also pressed on the need to introduce some long term and short-term measures to make the justice delivery system better.

Cybercrime is constantly finding new ways to wreak havoc, steal your private information, and commit all kinds of mischief. New technologies such as artificial intelligence (AI) and machine learning (ML) have already been leveraged by hackers and cyber criminals for their malicious intents. "At the heart of the Internet culture is a force that wants to find out everything about you. And once it has found out everything about you and two hundred million others, that's a very valuable asset, and people will be tempted to trade and do commerce with that asset." Join nearly 200,000 subscribers who receive actionable tech insights from Techopedia.

In addition to the traditional task of getting machines to answer questions, a major research question in question answering is to create interesting, challenging questions that can help systems learn how to answer questions and also reveal which systems are the best at answering questions. We argue that creating a question answering dataset---and the ubiquitous leaderboard that goes with it---closely resembles running a trivia tournament: you write questions, have agents (either humans or machines) answer the questions, and declare a winner. However, the research community has ignored the decades of hard-learned lessons from decades of the trivia community creating vibrant, fair, and effective question answering competitions. After detailing problems with existing QA datasets, we outline the key lessons---removing ambiguity, discriminating skill, and adjudicating disputes---that can transfer to QA research and how they might be implemented for the QA community.

Fine-tuning language models, such as BERT, on domain specific corpora has proven to be valuable in domains like scientific papers and biomedical text. In this paper, we show that fine-tuning BERT on legal documents similarly provides valuable improvements on NLP tasks in the legal domain. Demonstrating this outcome is significant for analyzing commercial agreements, because obtaining large legal corpora is challenging due to their confidential nature. As such, we show that having access to large legal corpora is a competitive advantage for commercial applications, and academic research on analyzing contracts.

If you shop online or occasionally speak to a voice assistant in the morning, you are already embracing the changes this technology has created. Many people are familiar with the advances of autonomous vehicles or facial recognition technology, and some may be curious, or even anxious, about how they will affect safety or privacy. Make no mistake, AI is a transformative technology that is influencing our daily lives and will touch every sector of the global economy. Whether society and government enable or inhibit the AI race, and the extent to which they do so, will be a critical question of the next decade. Regardless of the answer, the technology will forge ahead.

Remember when researchers predicted that professional services jobs in industries like insurance, tax and accounting, and finance and legal would soon be replaced by artificial intelligence (AI)? That was in 2013 when AI was just starting to peak on the hype cycle, and headlines like "Your Next Accountant Will Be a Robot" and "The Robots are Coming for Wall Street" were being cooked up daily. Today, six years into the evolution of AI in professional services, it's safe to say that the dystopian version of the future has not materialized. In fact, according to the latest data from the U.S. Bureau of Labor Statistics, employment of accounting professionals is projected to increase 10% over the next 10 years, which is faster than average for all other professions. In fact, there is a growing talent shortage in the industry that has many large and mid-size accounting firms struggling to fill open roles.

This op-ed originally appeared in Real Clear Markets on October 30, 2019. Robots have been coming for and successfully eliminating jobs for a long time: ask the iceman, elevator operator, or travel agent (if you can still find one). But what happens when the robots come for your job, succeed, and your job remains? Sounds strange but consider the conflicting reality of bank tellers and the robot designed to replace them: the Automated Teller Machine (ATM). The first ATM appeared in America in 1969.