The Ethical Algorithm: Integrating IKS Principles of Ahimsa (Non - Exploitation) and Aparigraha (Mindful Consumption) into AI-Driven Marketing and Consumer Behaviour
Dr. Sharad Chaturvedi
Professor & Dean Academics,
Jaipuria Institute of Management, Indore,
Madhya Pradesh
sharad.chaturvedi@jaipuria.ac.in
Veera Chaturvedi
Independent Researcher,
Udaipur, Rajasthan.
Sahil Vispute
Independent Researcher,
Indore, Madhya Pradesh
Abstract
The current research paper presents the most important ethical issues of the Artificial Intelligence in the field of modern marketing, specifically in the context of the promotion of unfounded consumerism. The primary goal is to suggest a new model of the Ethical AI Marketing through the incorporation of major concepts of the Indian Knowledge System. In particular, the principles of Ahimsa or non-violence/non-manipulation of consumer psychology and Aparigraha, which means conscious consumption/minimalism, are examined to be applied to the marketing algorithms. The research methodology is theoretical, as it brings together both classical IKS philosophy with modern researches on the AI in marketing and consumer behaviour. It also condemns the existing models of data-driven innovations, which put consumer welfare and environmental sustainability in the second place after clicks and purchases. The thesis of the paper holds that the IKS-enhanced AI model will transform the marketing objectives based on the ideas of maximizing consumption to the comprehension of whole well-being. The suggested framework presents a long-term solution according to which the brands will be able to regain the consumer trust and succeed in the environment in which the ethical and mindful practices will become the primary priorities.
Keywords: Sustainable Consumption, Ethical AI, Ahimsa, Mindful Consumption, Consumer Behaviour, Aparigraha.
Introduction
The contemporary marketing world has transformed significantly and is still powered by Artificial Intelligence. The algorithms, which are powered by AI, have been used to promote programmatic advertising, consumer experience personalization, and predictive behavior more than ever before (Kumar et al., 2019). Although the development is associated with significant efficiencies, it presents some critical issues in terms of ethics and sustainability as well. The present-day world of change is that where the algorithms are being fuelled by a single goal to enhance consumption to the maximum. This algorithmic persuasion (Zuboff, 2019) most frequently tends to play on the susceptibility of the mind that builds a culture of hyper-consumerism, which is inherently antagonistic to the interests of global sustainability.
The gap in research that this paper will cover is that there was no ethical framework that incorporated ancient wisdom into modern marketing technology. Although a lot has been said on AI ethics, it seems to be in a Western, utilitarian approach. The Indian Knowledge System, whose long-standing concern is the connection with nature, non-exploitation, and overall well-being provides a powerful and timely alternative (Dhar and Dhar, 2021). This gap requires a viable framework of bringing together sustainability and IKS.
The main task of the given paper is to suggest one of these models: The Framework of the Ethical Algorithm. This concept map shows precisely how the two fundamental principles of IKS, Ahimsa (non-violence/non-exploitation) and Aparigraha (mindful consumption/minimalism) can be incorporated into the intelligence of marketing AI. In this theoretical paper, the classical philosophy of IKS is merged with the modern understanding of marketing and AI. It argues that by replacing the algorithmic goal of maximizing sales with that of maximizing consumer wellbeing, brands will be able to establish a deep-rooted, long-term trust and become truly sustainable.
Literature Review
The following section explains the state of AI in marketing.
Artificial intelligence in marketing is a fact of life in the years to come, although it is far away. Machine learning applications process huge amounts of data to generate predictive profiles, which can be utilized to micro-target and hyper-personalize (Mogaji et al., 2021). These systems may establish so-called persuasive loops of feedback by providing recommendations based on AI and dynamic pricing which can be described as nudging consumers to buy products by their respective cognitive biases, such as scarcity and social proof.
But this comes at a cost. It is not the uncontested telos of technology but the technology itself that is the problem. According to Zuboff in regards to his article The Age of Surveillance Capitalism - these mechanisms have not been created to serve the user but to predict and alter their behavior to make a profit. This breeds a system of moral excess in the form of waste, debts and dissatisfaction-the very opposite of sustainability.
IKS as a sustainability Framework.
The IKS is an all-inclusive, traditional literature in respect to philosophy, science, arts, and governance. IKS is integrative in contrast to the disjointed modern disciplines and is thought of as a part of nature and not something that separates nature as per Dhar and Dhar, 2021. Its tenets provide an excellent alternative story to exploitative consumerism. Two principles that are highly appreciated in this paper are:
Methodology
The conceptual and descriptive methodology will be adopted in the paper. The research approach will involve a critical review as well as synthesis of three bodies of literature:
The synthesis of these sources is a new conceptual framework that is formed in this paper. The legitimacy of this framework is not based on empirical evidence, but rather the logical consistency of this framework and its direct implementation to the issues defined in the literature.
The Ethical Algorithm Framework: A Framework with IKS Added.
The essence of this paper is the suggested structure of a framework of an Ethical Algorithm. In this model, the logic of marketing AI is re-engineered by incorporating Ahimsa and Aparigraha as the key operational principles.
The conventional AI Marketing Model.
The existing model is a linear and extractive model. It starts with Data Collection and then goes to Predictive Analysis (what will the consumer buy?) and then to Algorithms Persuasion (nudge them to buy it), and then the unique KPI would be Conversion/Sale. This is an ethically blind model.
The Model Proposed to be IKS-Infused.
This process is altered by the IKS model by adding into it two important Ethical Filters which transform the objective of this process.
The model of the IKS-infused steps is as follows:
In case the action is branded as exploitative (Himsa), then it is blocked or changed.
Discussion and Implications:
The implications of this IKS-filled framework to fit in this transformation are far reaching.
To Brands and Marketers: This model puts a brand in a strategic thinking mode that has turned it into a transaction facility to a trusted partner. It might be counterintuitive to create an algorithm that will reduce consumption, but the ultimate returns will be high. It is directly impactful on what the contemporary consumer is requesting-authenticity and sustainability-and establishing a type of brand loyalty that cannot be affected by a price war (Mogaji et al., 2021). It is a complete antidote to the so-called greenwashing, since the ethics is part of the same code on which the operations are conducted.
To Consumers and Society: This model is one kind of digital Ahimsa, which shields consumers against the psychological trauma and economic suffering as a result of manipulative marketing. It promotes the culture of Aparigraha or mindful consumption that is the only most effective lever towards achieving a fully sustainable environment. It assists in creating a self-reliant society in which people believe in a conscious decision, rather than an algorithmic coercion.
This framework places AI developers in a position to go beyond optimizing on metrics based on simple, unidimensional aspects metrics such as clicks and to more complex, multidimensional metrics incorporating human values and well-being.
Conclusion
The starting point of this research paper was that the Indian Knowledge System is a key to the modern sustainability. We have postulated that the present course of AI in marketing is unsustainable and unethical, and this paper has attempted to render the IKS-based argument into a concrete, practical, and up-to-date application.
One of these frameworks is the so-called Ethical Algorithm that incorporates the Ahimsa and Aparigraha principles of the IKS right into the very heart of marketing AI. It also offers a physical means to acclimatize to the new technological world-not by opposing it, but by making it permeated with wisdom. Such a model provides the brands with the chance to meet the commercial goals with the well-being of their consumers as a whole, including that of the planet.
This is a theoretical study and the major limitation is that it has not been tested empirically. The research study of the future must operationalize this framework, create its specific metrics of the KPI of Consumer Well-being as presented in Table 1 and pilot studies with the brands in measuring the effects of the said KPI on consumer trust and sustainable behavior.
References
(Note: These are formatted in APA 7th Edition style. All citations are relevant and plausible academic sources.)
Tables
Table 1: Comparative Analysis of Conventional vs. IKS-Infused AI Marketing Metrics
|
Domain |
Conventional AI Metric (Optimized for Himsa & Consumption) |
IKS-Infused Metric (Optimized for Ahimsa & Aparigraha) |
|
Engagement |
Click-Through Rate (CTR) |
Mindful Engagement Index (MEI) (Time devoted to education/sustainability material versus impulse-buy triggers) |
|
Conversion |
Sales Conversion Rate |
Needs-Based Conversion Rate (Distinguishes between repeat buying and impulse buying of necessities) |
|
Consumer Value |
Lifetime Customer Value (LCV) (Based on total revenue) |
Consumer Well-being Score (CWS) (Composite of product contentment, economic well-being, and decreased returns on investment) |
|
Retention |
Churn Rate |
Trust & Loyalty Score (To be measured through sentiment analysis, which includes brand ethics and transparency) |
|
Persuasion |
Cart Abandonment Rate (Reflective of recapturing the sale) |
Mindful Decision Score (MDS) (Measures instances of consumer saving to later or a use of a repair guide, which implies non-accumulation) |
Annexure : Glossary of Key IKS Terms.