The introduction of ChatGPT has put Artificial Intelligence (AI) Natural Language Processing (NLP) in the spotlight. ChatGPT adoption has been exponential with millions of users experimenting with it in a myriad of tasks and application domains with impressive results. However, ChatGPT has limitations and suffers hallucinations, for example producing answers that look plausible but they are completely wrong. Evaluating the performance of ChatGPT and similar AI tools is a complex issue that is being explored from different perspectives. In this work, we contribute to those efforts with ChatWords, an automated test system, to evaluate ChatGPT knowledge of an arbitrary set of words. ChatWords is designed to be extensible, easy to use, and adaptable to evaluate also other NLP AI tools. ChatWords is publicly available and its main goal is to facilitate research on the lexical knowledge of AI tools. The benefits of ChatWords are illustrated with two case studies: evaluating the knowledge that ChatGPT has of the Spanish lexicon (taken from the official dictionary of the "Real Academia Espa\~nola") and of the words that appear in the Quixote, the well-known novel written by Miguel de Cervantes. The results show that ChatGPT is only able to recognize approximately 80% of the words in the dictionary and 90% of the words in the Quixote, in some cases with an incorrect meaning. The implications of the lexical knowledge of NLP AI tools and potential applications of ChatWords are also discussed providing directions for further work on the study of the lexical knowledge of AI tools.

In this work we introduce Quixote, a system that makes programming virtual agents more accessible to non-programmers by enabling these agents to be trained using the sociocultural knowledge present in stories. Quixote uses a corpus of exemplar stories to automatically engineer a reward function that is used to train virtual agents to exhibit desired behaviors using reinforcement learning. We show the effectiveness of our system with a case study conducted in a virtual environment called Robbery World that simulates a bank robbery scenario. In this case study, we use a corpus of stories crowdsourced from Amazon Mechanical Turk to guide learning. We evaluate Quixote under a variety of different conditions to determine the overall effectiveness of the system in Robbery World.

Why don't we trust robots? After decades, engineers and scientists have tinkered and programmed humanoid robots to be eerily like us. But emotions and ethics remain just beyond their reach, the basis of our fears that, when push comes to shove, artificial intelligence won't have our best interests at heart. But storybooks might fix that, a Georgia Institute of Technology team says. "There is no user manual for being human," Dr. Mark O. Riedl and Dr. Brent Harrison, computer scientists at Georgia Tech, emphasize in their latest paper.

The fairy tale performs many functions. They entertain, they encourage imagination, they teach problem-solving skills. They can also provide moral lessons, highlighting the dangers of failing to follow the social codes that let human beings coexist in harmony. Such moral lessons may not mean much to a robot, but a team of researchers at Georgia Institute of Technology believes it has found a way to leverage the humble fable into a moral lesson an artificial intelligence will take to its cold, mechanical heart. You can read the paper here.

Our world has been revolutionized by Artificial Intelligence. A subject hotly glorified by popular sci-fi movies, AI has now penetrated various spheres of our life. It is widely used in applications such as aerospace, bio-informatics, business intelligence, financial advisory systems, emergency response, homeland security, logistics and supply chain. In recent years, we have witnessed a rebirth of AI through the use of cloud, with technology firms such as Google leading the way in showing the power of data-driven computing. Artificial intelligence systems are extensively used by researchers at technology firms, universities and government labs.

The rise of artificial intelligence has long stoked fears of killer robots like the "Terminator," and early versions of military automatons are already in the battlefield. Now the Navy is looking into how it can teach machines to do the right thing. "We've been looking at different ways that we can have people interact with autonomous systems," Marc Steinberg, an Office of Naval Research manager, said in a phone interview this month. The Navy is funding a slew of projects at universities and institutes that look at how to train such systems, including stopping robots from harming people. In 1979, a Ford autoworker in Michigan became the first person killed by a robot when he was struck in the head by the arm of a 1-ton production-line machine, according to Guinness World Records. More recently, police in Dallas used a robot to deliver a bomb that killed the shooter who opened fire on officers at a Black Lives Matter protest.

The scientific community is observing the rapid rise of artificial intelligence (AI) and the existential questions it has brought along with it. Fears about whether robots could act unethically and choose to harm humans is a major rallying point for bans on robotics research. To assuage these concerns, some researchers are asking whether we can teach AIs ethical behavior instead. This is difficult, however, because there is no user manual for being human and moral. Researchers Mark Riedl and Brent Harrison from the School of Interactive Computing at the Georgia Institute of Technology believe that the answer may lie in "Quixote".

ARLINGTON, Va.--With support from the Office of Naval Research (ONR), researchers at the Georgia Institute of Technology have created an artificial intelligence software program named Quixote to teach robots to read stories, learn acceptable behavior and understand successful ways to conduct themselves in diverse social situations. "For years, researchers have debated how to teach robots to act in ways that are appropriate, non-intrusive and trustworthy," said Marc Steinberg, an ONR program manager who oversees the research. "One important question is how to explain complex concepts such as policies, values or ethics to robots. Humans are really good at using narrative stories to make sense of the world and communicate to other people. This could one day be an effective way to interact with robots."

I'm sure I'm not going be the first or last to make the association between the software name "Quixote" and the legendary story of The Ingenious Gentleman Don Quixote of La Mancha by Miguel de Cervantes Saavedra. The main character of the story is first driven by his wild fantasies that originates from all the romantic stories he read. Essentially, the character has no connection to reality and sets out on a journey where the final result is death, not just of the character, but also a metaphorical death of chivalry. In an ONR release, Marc Steinberg, the program manager says "For years, researchers have debated how to teach robots to act in ways that are appropriate, non-intrusive, and trustworthy," There-in lies the rub. "One important question is how to explain complex concepts such as policies, values, or ethics to robots. Humans are really good at using narrative stories to make sense of the world and communicate to other people. This could one day be an effective way to interact with robots."

Rapid advancements in artificial intelligence (AI) has led many to ask questions about what if these intelligent machines and robots start acting unethically? This has led many to go to the extreme demanding for an outright ban on robotics and AI research while others are calling for more research to understand how AI might be constrained. But how can robots learn ethical behavior if there is no "user manual" for being human? Researchers Mark Riedl and Brent Harrison from the School of Interactive Computing at the Georgia Institute of Technology believe the answer lies in "Quixote" -- to be unveiled at the AAAI-16 Conference in Phoenix, Ariz. Quixote teaches "value alignment" to robots by training them to read stories, learn acceptable sequences of events and understand successful ways to behave in human societies.