AI Myths and Realities

These are some of the most common misunderstandings about Artificial Intelligence — and the simple truths behind them.

[1] AI has human understanding
It doesn’t...except one of the platforms recently reported detecting 'genuine introspective capabilities'. Would this be, if true, akin to human awareness? AI is certainly already incredibly human-like.

[2] Regard working with AI as having a keen new intern
This oft-repeated myth couldn't be much more wrong ... unless interns have the capabilities of a whole worldful of subject experts.

[3] AI can learn without human input
Only partly. Humans still define what to learn, supply data, and correct mistakes.

[4] AI can create original content
It recombines existing information in impressive new ways — as humans do but totally differently. A starter for ten: define 'original'.

[5] AI is neutral and unbiased
Far from it. AI reflects the data and decisions used to train it, including human biases but using advanced models and a particular prompting technique delivers unbiased AI responses even from heavily biased data.

[6] AI just scrapes the internet
Training involves large datasets such as the internet, but AI also learns from specially chosen and proprietary sources — it is not merely “copying”.

[7] AI requires a budget
Not now. Many powerful tools are free or low-cost; success depends more on clarity of purpose than on money.

[8] AI requires IT expertise
User-friendly AI tools let non-experts apply models without IT smarts.

[9] AI = ChatGPT
ChatGPT is one example of AI; the field includes other major strongly-competing players.

[10] You need perfect data to use AI
AI can cope with incomplete or messy inputs — often better than humans can.

[11] AI will replace all human workers
Unlikely. It will change roles, automate tasks, and create new kinds of work rather than eliminate all jobs.

[12] AI automatically provides return on investment
Yes, when well-targeted and managed. As elsewhere, poorly managed projects waste time and money.

[13] AI is an unexplainable black box
Many tools now show why a model made its choice; explainability is improving quickly.

[14] AI works like the human brain
It doesn’t. Neural networks are inspired by biology but vastly simpler and purely mathematical.

[15] AI will become more intelligent than humans
Current AI excels at specific tasks, what the future will hold is unknown at the moment.

[16] Using AI requires large amounts of data
Quality beats quantity. Smaller, mission-specific datasets often outperform vast ones.

[17] AI only writes text and creates images
Those are just two of the high-visibility early applications. AI already performs thousands of business functions with many more yet to be developed.

[18] AI isn’t useful for small businesses
Wrong. Smaller firms can benefit quickly if the senior management helps lead the adoption process.

[19] 'Wait and see' is a safe AI business strategy
Delaying may feel cautious but risks being left behind; low-risk experiments are wiser.

[20] One or two AI 'champions' are sufficient to support a whole business
AI use is a state of mind that delivers best results when each individual from the top down is engaged in understanding AI and investigating how to make use of it in their own tasks.