Tulevaisuuswiki / Työn tulevaisuus
Paid Learning
Also known as Jobi Learning, Skill Investment, Palkallinen oppiminen
Paid Learning (Finnish: palkallinen oppiminen) is the practice in the Jobi Economy of paying participants in jobis to acquire skills when AI Work Matching predicts that the resulting increase in future earnings will exceed the cost of the training. Introduced nationally in 2031 and funded through the Verus, it has largely replaced the earlier distinction in Finland between working and studying for adults.
Principle
Paid Learning treats training as an investment in human capital. If teaching a participant a skill costs 300 jobis and is expected to increase that participant's lifetime output by 4,000 jobis, financing the training benefits both the participant and the wider system, which recovers the investment through verus collected on future transactions. The participant therefore receives income while learning.
Selection
Training recommendations are based not only on what a participant wishes to study but also on which local unmet needs the participant could become particularly good at meeting. The factors considered include:
- existing abilities;
- demonstrated learning speed;
- local demand;
- expected future prices;
- adjacent skills;
- individual preferences (see Lifetime Earnings + Fun).
Forms
On-the-job learning
Much Paid Learning takes place during productive work. AI guidance allows a participant to undertake a task somewhat beyond their current competence while receiving step-by-step instruction, and the level of assistance decreases as competence grows. In such cases the distinction between training and production becomes difficult to draw.
Structured study
For skills that cannot be acquired through task work alone, such as regulated professions, participants receive jobi payments while studying in vocational institutions, universities of applied sciences and universities. Payments are conditional on progress.
Career pattern
Paid Learning is the principal mechanism through which participants move from generic, low-priced tasks to specialized, higher-priced work. Repeated cycles produce what is described as the characteristic jobi career: undertaking a task, discovering an aptitude, training, specializing, earning more, and training again.
Right to exploration
Predictive funding of education raises evident risks. The system's assessment of a person's potential may be mistaken, historical data may reproduce existing inequalities, and a system that predicts a low return from educating someone may bring about the low return it predicted.
The Act on Algorithmic Work Allocation of 2032 therefore established a right to exploration: every participant is entitled to a minimum amount of publicly funded learning each year, regardless of the model's assessment of the expected return.