No one doubts that generative AI is the next big thing in tech.

But all that promise comes with a dark side that’s prompting organizations of all types to ponder the ethical implications of using it.

To some, it’s an ominous minefield. But it doesn’t have to be. 

As with any generational shift in technology, the rapidly growing influence of artificial intelligence on day-to-day life also introduces its own language.

Even as we experiment with chatbots like ChatGPT or Google Bard to get a better sense of what they’re capable of, we’re also challenged to learn a seemingly ever-expanding list of terms and definitions.

Perhaps to a degree greater than previously seen, understanding the subtle and unsubtle meanings of this essentially new language is critical to getting the most out of AI.

With this in mind, we’ve surveyed some of the most respected sources of computer science thought leadership and have compiled an initial glossary of terms. Check it out.

Should developers fear the emergence of artificial intelligence?

Will AI replace the need for humans to craft robust, efficient, and elegant code?

One software company CEO thinks curiosity is infinitely preferable to fear, and his developers are already reaping the rewards.

It’s no understatement to say that Geoffrey Hinton is as close to a god as we’re ever going to have in the Artificial Intelligence space.

The British-Canadian computer scientist and cognitive psychologist literally wrote the book on machine learning, after all. Along with AI rock stars Yoshua Bengio and Yann LeCun he picked up the 2018 Turing Award, the Nobel Prize for computer science, for creating the very building blocks of today's large language models (LLM).

Hinton is widely credited with creating the foundations of deep learning, which defines how LLMs are trained and how they synthesize and connect the data. So, his decision to quit his very plush job with Google so he could ring the alarm bells about AI means we should all stand up and take notice.

We can’t afford to ignore him. 

Over 1,100 of some of the most influential names in the artificial intelligence space last week signed a letter asking for a 6-month pause in training next-generation AI systems.

They warn the technology poses “profound risks to society and humanity.”

Should humanity listen to them and slam on the brakes? The answer to this question, as is almost always the case with anything related to AI, is complicated. 

OpenAI’s ChatGPT has been justifiably generating headlines – and controversy – since it was first released to the public in November 2022.

The ink is barely dry on this first chapter of the artificial intelligence revolution, and already a second chapter is well underway.

Hold onto your hats, because for better or worse, AI is now coming for your productivity apps. 

Do artificial intelligence-driven chatbots like OpenAI’s ChatGPT represent a mortal threat to the very future of knowledge workers?

Or do these virally popular examples of generative AI simply represent another specimen of disruptive technology that opens up new opportunities to move humans further up the value chain?

The answer, as with most things in tech, is more complex than it might initially seem. But it’s becoming increasingly clear that no one can afford to ignore the debate. This is no time to opt out of AI: it’s coming for us whether we like it or not. And while its impact on businesses, careers, and society at-large promises to be fundamental, it just as likely to not be as apocalyptic as the naysayers fear. 

Like it or not, data collection technology is pervasive. Your online activities and purchases are tracked. Your travels are monitored, and your location history is stored. Cameras regularly capture your image in public places. Now, technology recently patented by Microsoft for the stated purpose of improving meeting efficiency in the workplace may soon be monitoring the effectiveness of your behaviour at work. The collected data is then used to evaluate meeting participants' body language and analyze the data collected to determine whether or not they are making significant contributions to the meetings they attend. Although this technology is still in its infancy and there are currently no indications of when, or even if, Microsoft plans to make it available for deployment in the workplace, concerns have been raised that it crosses a line and that, if widely implemented, it could result in changes that will negatively impact a significant percentage of the working population.

How It Works

Using sensors, cameras, and software algorithms, Microsoft's "Meeting Insight Computing System" (MICS) will collect data on each meeting participant's body language, expressions, and participation level. MICS will also track how much time attendees spend on activities that are not meeting-related, such as texting or reading email. For remote meeting participants, MICS factors in whether or not they activate their cameras. The system will also take environmental factors into consideration, including the temperature and level of noise in a meeting room. Meeting time is also considered. A hot meeting room, a room with a distracting level of noise, or a meeting running into lunch hour could affect the attendees' levels of participation.

Many of the biggest technology companies (like Google and Microsoft) are investing heavily in artificial intelligence (AI) technology that will someday soon reshape business. According to Fortune Magazine, companies will invest over $50 billion/year by 2023 - and artificial intelligence will add more than $13 trillion in economic growth by 2030. This massive growth in AI spending will transform the way that companies do business.

1. New Capabilities Will Get Added to Existing Job Roles

Despite all the hype about AI eliminating millions of jobs, most human jobs will be fine. For example, before 2020, AI has created 2.3 million new jobs while only eliminating 1.8 million jobs. According to experts, AI removes repetitive tasks to allow employees to focus on more productive tasks. Therefore, new roles are being created for human workers to perform that increase productivity.

2. Companies Will Hire More AI Professionals

In addition to most human jobs being safe, many businesses will have to hire more AI professionals. For example, most machine learning platforms are built and run on Python. Therefore, the demand for computer programmers with Python experience is growing. Other new job opportunities will include data analysts who can manage massive amounts of enterprise data.

It was not long ago that artificial intelligence (AI) was purely the stuff of science fiction. The entertainment industry has profited greatly from our natural tendency to trust new AI tech, with popular movies like War Games and the Terminator series painting a bleak, dystopian vision of the future. A future where omnipresent robots run wild and human beings are both expendable and subject to the will of sinister machines.

However, many artificial intelligence advancements have already been integrated seamlessly into our modern day-to-day existence. From nanobots assisting with medical procedures to complex traffic management, AI developers are devoted to using increasingly ubiquitous technology to improve quality of life.