W2: Quaquebeke & Gerpott (2023) Flashcards
(14 cards)
“True” leadership
Motivating and enabling people so that they can and will contribute to the collective goals of an organisation
Article’s purpose
Delineates why algorithms will not (need to) come to a halt before core characteristics of leadership and potentially cater better to employees’ psychological needs than human leaders. The paper explores how sophisticated algorithms can embody the core characteristics of leadership. Specifically, that technology is moving from a tool for human leaders (NOW), to an proactive advisory/support role for human leaders (NEW), to eventually substituting for human leadership (NEXT)
NOW of leadership
Digitalisation in leadership refers to digitally mediated communication and the associated challenges of leading a remote or hybrid workforce. Technology in the NOW of leadership is merely about translating traditional leadership to a digital space. While certain aspects of leadership may be more relevant than others in such virtual or hybrid working, the prevalent issues are not radically new
NEW of leadership
Concerns how algorithms can effectively and proactively augment or support leadership, such that humans and AI collaborate in leading employees. This augmented leadership approach is also known as the AI serving as a partner or co-leader, with algorithms making suggestions about what leaders should look at, which team members may require more attention, or how to improve team dynamics. Such an AI-supported leadership approach is mostly adopted by start-ups offering sophisticated technological solutions to help leaders in core responsibilities. Thus, AI-based leader-support dashboards or communication assistance systems will soon become more mainstream
Task-related leadership
Includes observing employees’ work progress, offering task-related advice, helping with problems, or contributing to effectively structuring the work process. AI-based solutions include feedback dashboards for leaders that provide them with high-frequency insights into team challenges and data-based recommendations for actions that could be undertaken to tackle these challenges. Even with such support, humans still have to consider what they want to be supported on and decide whether they want to follow the advice of AI or not
Relation-oriented leadership
Functions comprise several facets. Some AI-based solutions are already in place, e.g. chatbot Amber. Such AI-based tools could be used in video calls to give leaders real-time information about whom to address to regain attention, who might be the “ringleader,” or what kinds of topics will cause employees to withhold their opinions
Chatbot Amber
An employee engagement tool that allows employees to share feelings. It provides leaders with real-time insights into their employees’ experiences, and its implementation gained momentum during the COVID-19 pandemic. It relies on automatic sentiment analysis and warns leaders via a dashboard, e.g. about disengaged employees, so countermeasures can be taken in a timely manner. It provides attrition risk and advices about whether and how leaders should intervene
Change-oriented leadership
Refers to formulating an attractive vision for employees, charismatically spreading enthusiasm and energy among followers, or initiating change. Here, leadership scholars often express the most reservations about whether and how AI could assist human leaders, e.g. an AI’s support in applying charismatic leadership techniques. These techniques are specific and well-defined, and an AI tool could easily provide leaders with inspiration about how to address their followers more charismatically. AI-based applications can thus help leaders envision sound strategic changes but also help translate these into concrete communicative actions, which could then even be personalised for different audiences
NEXT of leadership
AI will not only support but substitute human leadership; completely assuming authority over task-, relations-, and change-oriented functions that people prototypically associate with human leaders. One of the main game changers will be that AI leaders can communicate better, but also address followers’ fundamental psychological needs. Thus, AIs will be able to cater to human nature and not just humans’ instrumental value for the business
Self-Determination Theory (SDT)
Has identified three basic psychological needs; (1) the need for autonomy, (2) for competence, and (3) for relatedness. According to SDT, meeting these supports human flourishing and lead employees to be more motivated to engage and more satisfied
Litmus test for AI leadership
Whether it can cater to the fundamental needs of SDT by effectively performing task-, relations-, and change-oriented leadership behaviours
Fulfilling employees’ needs for autonomy
Algorithms can provide a lot more individualised real-time information transparency than human leaders. AI leaders can make employees feel more in control of their work, and thus increase intrinsic motivation. E.g. AI leaders can increase autonomy by sending messages that inform them about potential actions while giving employees the opportunity to substantiate their own positions
Fulfilling employees’ needs for competence
A leader is expected to teach and guide employees by honing their sense of mastery. The transparency guaranteed by an AI leader can empower employees to try out new ways of working and directly see the results of their actions. Thus, an AI leader can use automated and individualised feedback systems to engage employees in real-time learning, thus sharpening their sense of competency and efficacy
Fulfilling employees’ need for relatedness
In the future, avatars of algorithms will be indistinguisable from those of real humans. Given that they can analyse patterns better and make logic jumps beyond linear relationships, AI leaders can, e.g. facilitate social connections at work by introducing colleagues to each other who have a high chance of getting along
