If virtual assistants impersonate a human, it can lead to poor experience and lack of trust with the brand. Virtual assistants are an extension of brands consumer experience. When dealing with virtual assistants, transparency often refers to informing the consumers who they are chatting with ie virtual assistant, not actual human, sharing details on what information can the consumer search, and how his data will be used, stored, analyzed for improving experience.īrands build trust with consumers by being transparent and honest in communication. In this section we interpret these principles with a view on virtual assistants and what considerations should designers, developers and consumers understand when developing and interacting with virtual assistants.ĪI transparency refers to the explainability, interpretability, disclosure of the algorithmic models including their training data, accuracy, performance, bias and other metrics. on the global landscape of AI ethics guidelines, they found globally five emerging ethical principles that are deemed important – Transparency, Justice and fairness, Non-maleficence, Responsibly and Privacy. ![]() In a recent paper published by Jobin, A., Ienca, M. Looking through the lens of ethical principles, other questions arise, beyond “What can the virtual assistant answer?” For example, “Does the answer promote consumers interests or business interests like recommending the most profitable product which does not best suited”. The focus is on intelligence of the system to respond to human questions. Ethical principles for virtual assistantsĪI based virtual assistants ability to act intelligently has long been evaluated by the Turing Test and Loebner Prize. In the last section, we look into what is the probable future of super intelligent virtual assistants.ģ. ![]() Further, we analyze the guidelines and legislations that companies and governments have published. Next we discuss different types of virtual assistants deployed today deep, dive into the technology and learning techniques that make them ethical. These principles provide key ethical considerations that designers and consumers should understand. In subsequent sections of this chapter, we first define “What is ethics?” and then discuss on ethical principles for virtual assistants. California “Bot Bill ” provides only limited protection for consumers in terms of bot self-declaration. Significant work has been done in the area of Ethically aligned design for Autonomous and Intelligent systems by IEEE and in the area of Facial recognition technologies but the area of virtual assistants has seen limited guidelines or regulation. Objectional discriminations can arise due to multiple reasons like wrongly defining the business objective of machine learning model, using unrepresentative data or data with existing prejudice for training or by selecting wrong attributes or features of the AI model. For example, the loan application algorithm gives higher credit scores to older males due to training bias. Although, AI by its very nature is a form of statistical discrimination (finding patters in data), the discrimination becomes objectional when it places certain privileged groups at a systematic advantage and certain unprivileged groups at a systematic disadvantage. One of the most important aspect in all guidelines is ethics, “AI should be ethical, ensuring adherence to ethical principles and values”. These guidelines provide a broad level objective for the use of AI – to ensure human-centric, safe, and trustworthy AI. Many countries have published AI policy guidelines. ![]() However, virtual assistants are built by humans using artificial intelligence (AI) technologies and have wide ranging ethical implications which are important for organizations and consumers to understand. Virtual assistants enable organizations to reduce costs, increase brand loyalty and better serve customers. They offer 24/7 service and fulfill the need of millennials for real time responses. Organizations are rapidly deploying Virtual Assistants aka bot technology for automating communication, customer service, conversational commerce, product recommendation, education support, financial services, medical services, entertainment, social outreach and self-service tasks.
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