Palkitsemismallin

Palkitsemismallin is a Finnish term that refers to the conceptual framework for designing and evaluating reward systems in organisations and artificial intelligence. The word is constructed from palkitse (to reward) and mallin (model), and thus literally means “reward model.” The concept has been used in both human resources management and machine learning literature since the late 1970s.

In the human‑resource domain, Palkitsemismallin describes a set of criteria, metrics, and incentive mechanisms that align employee behaviour with organisational objectives. Common elements include performance appraisal, bonus schemes, recognition programmes, and non‑monetary rewards such as professional development opportunities. Researchers have studied the psychological impact of different reward models, finding that intrinsic motivators often produce more sustained engagement than extrinsic financial incentives.

In artificial intelligence, Palkitsemismallin is applied in reinforcement learning to define the reward function that guides agent behaviour. The model specifies what constitutes a successful outcome, how rewards are quantified, and how they are propagated through time. Discussions in the AI community emphasize the importance of shaping reward functions to avoid unintended consequences such as reward hacking or excessive risk‑taking.

Variants of Palkitsemismallin exist in many languages and sectors. In corporate settings it is often called compensation models, while in machine learning it is simply referred to as the reward function. Both usage contexts share the same foundational principle: the systematic design of incentives to steer desired actions.