Privacy threats:
- Data leakage and resale
Manipulation of consciousness:
- Fake news and deepfake
- Targeted advertising
Discrimination and bias:
- Algorithmic injustice
- Unequal access
Automation and unemployment:
- Replacing human labor: AI replaces people from professions, increasing social inequality.
- Economic imbalance: AI technology owners get richer, the rest lose income.
Loss of humanity:
- Degradation of communication: chatbots replace live interaction.
- Emotional exploitation: AI imitates feelings (e.g. virtual partners), affecting the psyche.
Increase user trust:
People are more willing to interact with AI if they are sure that their data is protected and algorithm decisions are fair.
Example: Banks using ethical AI for credit scoring, get more loyal customers.
Reducing the risks of discrimination:
Ethical AI minimizes bias in decision-making
(e.g. when hiring or approving loans).
Example: IBM has developed tools to identify and eliminate bias in algorithms.
Improving companies reputation:
Companies implementing responsible AI,
attract investors and customers who care about ESG values.
Example: Google and Microsoft publish ethical AI principles to avoid scandals.
Compliance and avoidance of penalties:
Regulators (EU, USA, China) already impose strict AI regulations (e.g., **EU AI Act**).
Ethical AI reduces legal risks.
More sustainable development:
AI can optimize energy consumption, reduce carbon footprint and help with environmental issues.
Example: Algorithms for smart cities reduce traffic jams and CO2 emissions.
Improving medicine and health care:
Ethical AI in diagnosis takes into account the diversity of patients, reducing errors.
Example: AI systems to help detect cancer al early stages without racial bias.
Supporting human values, not replacing them:
Instead of full automation, ethical AI complements people's capabilities (e.g. helps doctors, but does not replace them)