India having witnessed a great leap in digital revolution, emerging technologies such as Artificial Intelligence (AI) could be explored to reduce corruption at various layers and departments of government.

AI could be used for anti-corruption efforts adopting both top-down or bottom-up approaches. While top-down approach is based on the view that institutions are shaped by the existing laws, bottom approach views institutions as emerging though customs, beliefs, traditions etc. Thus, while the former requires serious involvement and efforts of the political leadership, latter is to be evolved and developed by civil society organisations, journalists and cultural organisations

Public procurement is a key area where AI could be explored for which digitisation of data on procurement is mandatory. The data on companies applying for bid, the procedures involved in bidding process till the award of tender could be effectively analysed for getting logical conclusion on malpractices prevalent in the system. India too had implemented GeM platform which could be further replicated across India integrating it with AI and data analytics tools.

AI and blockchain technology can be used to combat corruption in the health sector. Pharma companies sometimes bribe doctors to get their medicine prescribed. This can be reduced through employment of AI and blockchain to facilitate information availability to patients on effectiveness of medicines. Digitisation of database of patients is key in this context with necessary inbuilt privacy tools through which patient can log in to understand the effectiveness of medicines of specific companies.

Real estate sector is another area where AI and data mining tools could be explored to identify outliers in the market, especially sudden and dramatic increase in housing prices, tax evasion etc. This requires digitisation of revenue records available with state governments coupled with simultaneous implementation of AI tools. Linking of revenue records across India may also facilitate detection of frauds as also ownership of benami property/transaction across States.

Application of AI across banks and financial institutions for fraud detection, suspicious transactions and financial crimes is key. The public distribution system is another vast area where AI could be explored to prevent leakages and identify suspicious transactions.

AI could be explored for analysing risk of corrupt behaviour of civil servants.

However, the challenges in this regard include getting the factual information from various sources and uniform maintenance of database structure across various states. Prediction of corruption could also be possible, based on cross section and time series data of a particular sector.

AI could also be explored for simplifying procedures, increase integrity and reduce interaction points ultimately reducing corruption. Most of the procedures related to day-to-day transactions are explained with the help of complex rules and regulations which could indeed be interpreted to suit various circumstances which ultimately ends in litigation, bribe and undue interference of courts. AI with the help of blockchain tools could simplify those with transparent procedures which are citizen friendly.

For application of AI, quality of data sets, coupled with skill to explain the datasets is imperative, which requires training for those involved in collecting and interpreting of data. Digitisation is another requirement with well-established and well-equipped software for maintenance, storage and interpretation of database.

Privacy concerns also need to be addressed with necessary data protection laws. Developing ethical guidelines for the design, application and promotion of trust in AI is equally important as technology develops faster than legislation in most of the cases.

The writer serves as Deputy Secretary, Ministry of Finance. Views are personal

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