The exponential growth of artificial intelligence provides unprecedented opportunities to mould human behaviour and decision-making through the concept of nudging in behavioural economics. Nudge theory suggests various ways in which human behaviour can indirectly be influenced by altering the environment, or choice architecture, so as to serve as a catalyst for some desired behavioural outcome by exploiting humans’ inherent cognitive biases. While advertisers have long known that the concepts of nudge theory can be used to influence decision-making, artificial intelligence provides new and more effective ways of doing so - for example, through targeted advertisements and manipulating search results through suggestive search engines. Conversely, artificial intelligence has also been used within organisations themselves with the aim of promoting productivity. In this article, I will argue that artificial intelligence can be effectively used to nudge users into better outcomes; however, there are risks associated with doing so. While there are notable benefits of utilising artificial intelligence to nudge consumers, from a consumer and producer viewpoint, there are also areas of potential hazard of doing so - examples including the issues of autonomy and manipulation.
By utilising algorithms that operate on big data (huge, diverse sets of information that grow at exponential rates), artificial intelligence fundamentally has the potential to surpass the effectiveness of non-AI nudging methods in that nudges can be customised for individuals and efficacy can be measured and adjusted as the algorithm learns from feedback data which monitors users’ decision-making behaviours. Hence, from the perspective of suppliers interacting with consumers, behavioural insights can be leveraged in order to ensure that consumers spend more money. In fact, chatbots have increased sales by an average of 67%, according to Gitnux. Another method of utilising artificial intelligence that we can look at is suggestive selling. Suggestive selling, in the form of suggestive searching, is a sales technique where a sales associate suggests additional or complementary products or services to a customer in their shopping experience, according to lightspeed. According to studies conducted, organisations that implement effective suggestive selling techniques observe a boost in revenue from around 10% to 30%.
In the sphere of healthcare, artificial intelligence can empower individuals to make more health-conscious choices and adhere to medical recommendations through personalised nudges administered through mobile apps, wearables, or virtual health coaches. For example, AI-driven health trackers are able to analyse and evaluate biometric data, identify patterns, and give personalised feedback and encouragement to motivate individuals in physical activity, medication adherence, and preventative care.
Furthermore, we can examine the role of the synergy between artificial intelligence and nudge theory within workplaces themselves. In particular, with the advent of conversational artificial intelligence and inputs from behavioural economics, employees’ efficiency and engagement can be bolstered. Conversational artificial intelligence refers to technologies - for example, chatbots or virtual agents - that users can interact with. We can observe the boost in productivity in the workplace from the fact that 40% of CEOs find AI-powered solutions helpful in improving employees’ skills, according to Gitnux. Conversational artificial intelligence platforms smoothly integrate into communication channels often used in the workplace, such as Slack and Microsoft Teams. Due to the paradigm shift in the way that employees interact with processes and organisational systems through leveraging generative artificial intelligence and natural language processing, employees can more efficiently access information and resolve inquiries. By taking advantage of insights from psychology and cognitive biases, organisations, via effective utilisation of artificial intelligence, can create environments which facilitate positive choices and actions. AI-powered chatbots or virtual assistants have the capability of delivering timely reminders, feedback, and incentives to employees, modified to address individual employees’ needs and fostering personalised behaviour change and habit development to increase productivity.
One example of how companies can do this is through the ‘chase pattern’, which provides employees with a more aggressive alternative to simple reminders. This proactive pattern actively seeks out an answer to a particular question, and if a user does not provide it, the bot will move to the next user or continue to repeat the inquiry until the answer is obtained and the criterion is met. This pattern has been applied to companies such as HomeAdvisor in order to ensure that contractors show up to appointments on time. In this case, HomeAdvisor recognised that their customers’ brand perception was contingent on whether their first hired contractor made it to the property on time. Through designing a bot with the chase pattern implemented, HomeAdvisor was able to remind and confirm appointment times with contractors to ensure that customers would have interest in remaining loyal to the company and hiring their contractors repeatedly. This is simply one example of many in the movement towards improved overall performance and operational efficiency in the workforce, with 81% of office workers believing that artificial intelligence pushes them to improve their overall performance in work and 61% of employees stating that ‘a more efficient and productive work day’ was a top benefit gained from using artificial intelligence, according to SnapLogic.
However, with the upwards trend of organisations incorporating artificial intelligence not only into producer-consumer interactions but also in the workplace, the resulting ethical, privacy, and transparency concerns must be considered alongside the positive potential. The opacity of artificial intelligence algorithms, especially considering that only one in every ten workers have specific skills related to artificial intelligence (according to CNBC), and the potential risk of algorithms developing biases result in hazards of unintended consequences and treatment that may be deemed unfair. Furthermore, the usage of artificial intelligence in nudging requires consideration of issues like autonomy, consent, and potential for manipulation - the question arises of whether it is ethical to be pushing consumers and employees alike in order to behave in a certain, pre-planned manner given that they may not have explicitly consented to do so (given how ingrained artificial intelligence nudging is becoming through methods like suggestive search engines). Ways of tackling these potential issues, such as the possible expansion of artificial intelligence beyond its intended usage (for example, through artificial intelligence developing biases), are often debated and contested - the issue of whether regulation should be in place to limit the pace of artificial intelligence growth, and the extent and coverage of this hypothetical regulation, are areas to look into further.
On balance, while the trajectory of artificial intelligence has a huge amount of potential in nudging individuals towards what are considered ‘better’ outcomes and harnessing principles of behavioural economics, the ethics, privacy, and transparency of implementing said changes must be considered. In particular, in the fields of healthcare and in the workplace, artificial intelligence has the transformative power to promote positive societal change. By integrating insights from nudge theory in behavioural economics, we can leverage this transformative power to create a healthier, more sustainable, and wealthier trajectory for individuals and organisations.
Writer: Ritisha Baidyaray
Editor: Ritisha Baidyaray
Kommentare