Model development was always a challenge in any subject but is more so in an area where abstraction is the foundational attribute: AI. I have written earlier also that abstraction is the first step to building great software and especially in AI, because AI works on abstraction, which depends on mathematics of the highest level. Most people will say data but what they forget is that the model needs data and vast amounts of it, precisely because it has to abstract from it so as to work effectively whatever be the data. The model abstracts from the data so that it can work on any data! This is the crux of any model.

A superior technology such as AI cannot wash away the sins of poor implementation which inevitably results in poor data quality and as source data to AI. Will this poor quality of data not escalate problems with the embedding of AI in an ERP software? Analytics, the darling of consultants for over a decade, could well become an unmitigated disaster. It is firmly established that poor data quality alone remains one of the principal causes of failures in the efficient use of AI systems. Interestingly, the database as the OS, an idea articulated by Professor Michael Stonebraker, could be the opening to a new way of looking

There is a continuing debate on ethics and AI. It is probably a premature debate because we have not even succeeded in addressing the serious and sustained problem of the lack of transparency and misuse for personal gain in contemporary information technology, especially as it is used in markets. The number and scale of recent scandals in crypto has put paid to the assumption that technology will usher in transparency. If anything, the contrary appears to be the stronger probability. The misuse of systems, any system, is not a new phenomenon.

There is an intensifying obsession in businesses with automation, aided and abetted by AI, which is so overpowering that it has displaced from the public sphere all else, displaying a poverty of thinking through. Since it is clearly not a phase, the sooner businesses realise the folly of such narrow thinking, the better it will be. Will they?

We don’t have to dramatically alter our educational system for AI as is being argued by many because there is no dearth of educational materials on subjects such as Linear Algebra, Calculus, Probability and Statistics, which, however, can be and are studied even without any reference to AI. And the same goes for language too. We need to reorient the study of these subjects from the perspective of AI and build also a new generation of teachers. It is vital that we apply our minds to this if we do not wish this endeavour to go the way of so many Edtech companies

What a relief! Humanity is safe from AI! AI is not going to take over humanity. For a simple reason.
There is a business to be built, actually businesses, competition to be ridiculed and quashed, new products to be launched, new names to be thought of (no more LLMs – Meta), pricing to be perfected, investments to be carefully planned. With so many practical things to be accomplished, where is the time to take over humanity?