Ever since we are dealing with mathematics and computers, we have come across a term — an algorithm. Algorithm is basically a rule that automates how a piece of data is handled. It brings classical logic to computing — If-then-else type of issues. If ‘z’ happens, do ‘x’. Else do ‘y’. After all, a computer programme is an agglomeration of several such algorithms. All these algorithms are strung though a logical sequence. It facilitates a certain result. These are simple operations on datasets. Computers perform such algorithmic functions at high speed.

Of late, algorithm has acquired a new meaning. There are algorithms that facilitate targeted advertising. The content offered on social media is based on the algorithms that predict the viewers’ likes. Radiological images are interpreted on the basis of algorithms. Generative AI works on predictions based on such algorithms. Some startups are funded on the basis of how they can beat the algorithm of large engines such as YouTube or Instagram.

Thus, algorithm’s lexical meaning has changed. We believe such algorithms can be changed by the organizations who create them. Gemini’s image generating capabilities have been criticized. Even text messages generated by the LLMs have attracted criticism. Can the firm fix this? In the field of AI, though the algorithm may have been initiated by a firm, the algorithm has the capability to learn and change itself. Those who own it can fiddle with it but they cannot completely control it. The functioning of these algorithms becomes a black box.

There are attempts to audit and modify these black boxes. However, these are not enough to control their going off the track and produce unacceptable results. There are limitations of such audits.

There should be complete access to the AI systems — access to its inner workings. There should be information about its development and deployment. There should be tests to see whether black box outputs consistently pass the discrimination tests. Thus, even when the logic inside the black box is irrelevant if the black box provides acceptable results, it is okay. Algorithmic results must be subjected to rigorous testing and audit.