AI Based Self Preferencing and Consumer Safety in Digital Market

This research paper elaborates the use of Machine learning and algorithmic self-preferencing in the digital market, specially in e-commerce. The artificial intelligence and machine learning based self preferencing are used by dominant player in the digital market to ranked their own products over the other products of independent seller. This is evident when consumer search for any products digitally. This paper elaborates with decided cases that how selfpreferencing distorts visibility, inflates prices, and entrenches market concentration. The response of the judiciary across the globe raised the concern on Self Preferencing by the abusing dominant position in the digital market. This paper also evaluates large societal harm that causes innovation suppression, consumer trust erosion, and concentration of economic and political power. This paper tries to address the challenges that ex-post antitrust enforcement, ex-ante regulatory obligation and regulation that govern the self preferencing. the paper argues that ensuring neutrality, transparency, and accountability in platform algorithms is essential to preserve fairness, innovation, and trust in digital marketplaces. This paper claim for the neutrality, transparency and accountability of digital platform providers in ecommerce to gage the trust and fairness in the competition.