Home / Tech  / What does Artificial Intelligence actually mean? We ask industry larks for their definitions

What does Artificial Intelligence actually mean? We ask industry larks for their definitions

Dr Helen Heath is a poet, novelist and technologist. Heath is the author of the book, Are Friends Electric, which focuses on the intersect between people and technology. 

Heath says, “I define AI as apparently intelligent behaviour indistinguishable from that of a human. It doesn’t really matter if it is actually conscious or not, only that we feel it is; humans are very good at projecting human traits onto even inanimate objects (of course, not everything we currently call AI is indistinguishable but we are getting there). The most interesting thing about AI is that it forces us to think about what truly defines us as humans and what it means to be a good human.”

Alex Bartley Catt is the founder of Artificial Intelligence company Spacetime.

Catt says,”When we talk about artificial intelligence today it is computer software, and we are speaking about a set of specific technologies from a range of tech companies including; IBM, Google, Microsoft, and Amazon. But the power in the computer software is the algorithms that allow them to complete tasks and make decisions. So, when we perceive these decisions or tasks performed by computers as intelligent or human-like, that’s when society starts using the term Artificial Intelligence.

“This means the technology we perceive as Artificial Intelligence is always changing, a computer beating the world’s number one chess player was once groundbreaking Artificial Intelligence, but not anymore.”

Justin Flitter is the Founder of NewZealand.AI, Tech.Kiwi, AI-DAY and host of The AI Show and monthly events showcasing the practical business applications of AI and Emerging Technology.

Flitter says, “An AI system is a machine designed to learn, to solve problems, to complete complex and repetitive tasks that previously only humans could do.”

“One aspect of AI is Machine Learning where programs are provided with sets of training data and parameters to learn patterns and serve up the best response. That could be as simple as Google Images knowing what is a Dog vs a Cat or as advanced as a program that can identity Breast Cancer cells 400% more accurately than humans.”

“The difference between AI and other computer software or big data applications is that ‘big data’ programs can present ‘Here are all the images tagged ‘dog’.’  where as Artificial Intelligent systems provide ‘Here are all the images with Dogs in them.’”

Sarah Hindle is general manager of Tech Futures Lab, which specialises in future-focused training, business coaching, masterclasses for professionals and home of New Zealand’s most innovative Master’s degree.

Hindle says, “Artificial intelligence is computer code that learns and adapts in a similar way to the human mind. It’s software’s super-charged cousin: the difference between the wind-up toy that will spin its wheels against a closed door and the robot that figures out how to open the door and let the cat in. With standard computer software, you need to learn its language. With artificial intelligence, it learns yours.

“The autonomous aspect of AI is what some find challenging. Debate rages even between leading tech exponents about whether to define AI as an opportunity or a threat but the fact is that it’s here. We’re using it every time we Google or summon Siri. What New Zealand businesses need to do (and fast) is get to grips with the potential of AI and how it will impact on their sector and their workforce. Our advice is always to start with the problem to be solved, rather than the technology. For example, we have Master’s students developing chatbots to help address time-zone or language barriers and stop brokers or middle-men from over-influencing decisions. AI-driven agents offer 24/7 customer service and can learn from an organisation’s existing data.”

To summarise, she says: “In an ideal world, AI, machine learning and data science will relieve us of the monotonous aspects of work and have potential contribute to more inclusive decision-making, but for this to happen, business leaders need to understand it and figure out how best to work with and alongside it.”                    

Review overview