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‘The future is going to come down to how we can make AI equitable’ – 25 quotes of the week on creativity, innovation & technology >

- by Madanmohan Rao [December 28, 2023]

WordSparks (‘words that spark change’) is a weekly feature from, featuring quotes from media around the world on creativity, innovation and technology (see our earlier compilation here). Share these gems and insights with your colleagues and networks, and stay tuned here for our next edition!

AI-powered tools can produce content much faster and more affordably than humans, making competition fierce for artists.

AI is omnipresent and will rearrange our thinking and discovery process, and shape our artistic and creative expression. It will question and change the creative process. In a way it will force us to be born again.

I’m more afraid of the devaluation of art than I am of a machine taking my job.

There may be a hit song that has a novelty to it because it was A.I.-generated, but what people love about music is authenticity.

There’s a lot happening that has profound implications. And it’s also an opportunity for growth if the moment is seized. If not, we might be looking at a future not unlike what occurred during the Napster period. There’s a chance to use these tools in a fun but equitable way.

As AI algorithms analyses vast amounts of existing art and data, there is a risk that artistic creations might become formulaic and predictable, imitating popular styles and trends rather than pushing the boundaries of originality.

Human [fashion] designers will remain key, while gen AI will enable their roles to be orientated around curation.

AI can analyze previous designs, generate novel design ideas, and test prototypes, assisting engineers with rapid, agile design practices.

Through the combined power of predictive analytics, generative AI, and high-resolution cameras, product quality issues that human vision might miss are proactively identified.

AI also plays a crucial role in ensuring the safety and quality of toys. AI-powered systems can inspect toys at various stages of production, identifying defects or potential safety hazards.

Without appropriate testing, risk mitigations and human oversight, AI-enabled tools used for clinical decisions can make errors that are costly at best - and dangerous at worst.

Even within clinical medicine, there's a huge emerging body of literature on how much these AI algorithms know about medicine—we still don't know how that translates to outcomes.

AI technology is evolving and there are many uses for it in healthcare, and reducing the global tuberculosis burden is one of them.

At the enterprise level, uncertainty around OpenAI's future may lead to organizations taking a step back to develop an AI strategy that isn't so dependent on a single platform–analogous to the multi-cloud strategy discussion.

Traditionally a slower adopter, biopharma is already using AI at scale from drug discovery to portfolio management, all the way to clinical trial design and delivery.

From helping teach English, to assisting teachers with lesson plans, to identifying pupils at risk of dropping out, AI tools are helping bridge learning gaps that widened in schools during the Covid-19 pandemic.

History tells us major changes in technological paradigms are often followed by periods of disruption, typified by economic growth and net job creation—an idea at odds with current concerns about job destruction in the wake of generative AI.

Proper use of AI minimizes the resource and equity gap among students by providing them with a tool that can be tailored to each as a unique individual.

By reducing the reliance on manual labor, these [AI] technologies are paving the way for a more efficient, sustainable, and productive agricultural sector.

Agriculture production is using technologies that now embed AI technologies. For example, drones or tractors, weeding or pesticides administration, and crop management.

The vision that we have is to replace guesswork with data and AI. And it’s not to replace a farmer but to augment the farmer’s knowledge with data.

In a world where societal shaming of sexual behaviours and increasing censorship are prevalent, the appeal [of these chatbots] lies in creating a space for open and judgement-free communication, even if it involves interacting with an AI.

We need to act now on young people creating AI indecent imagery, before it’s too late.

Despite the hype surrounding generative AI, we aren’t heading towards a ‘rise of the machine’ scenario in legal. There are many issues to iron out – from hallucinations and security to ethics, data management, and regulation – which means that human intellect is very much indispensable.

The future is going to come down to how we can make A.I. equitable.

Madanmohan Rao is Co-founder of, and author of 15+ books on innovation, knowledge management, and digital transformation. He can be followed on LinkedIn and Twitter