Table 4 Expert assessment of discrepancies and recommendations for response (St. 15)
Discrepancies in innovations contributing to the use of digital technologies to make nutritional decisions and the sharing of data with doctors, employers or insurance companies (in Germany) | |
Reasons for higher probability | - The costs of poor nutrition are rising rapidly. Therefore, preventive measures and treatments are being pursued |
- The value of data for businesses is tempting | |
- Insurance companies and employers provide incentives for customers to share their nutritional and health related decisions, e.g., with bonus campaigns or reduced rates | |
- Interest in learning about one's own state of health | |
- Labor shortages are driving digitalization (e.g., in the health sector) | |
- Desire for self-optimization coupled with too little self-assessment in society | |
Reasons for lower desirability | - Data on dietary choices can be used to influence consumers |
- With increasing transparency, a decline in consumer autonomy can be expected | |
- Social cohesion (e.g., community and solidarity) can decrease (e.g., if the control of eating habits affects social benefits or access to career opportunities) | |
- Loss of freedom of choice: Possible exclusion and disadvantages if an individual does not want to participate | |
- Data protection issues could lead to exclusion of specific social groups (e.g., based on physical conditions) | |
Options for "avoiding harm" with innovations contributing to the use of digital technologies to make nutritional decisions and the sharing of data with doctors, employers or insurance companies (in Germany) | |
Institutions, Structures & Procedures | - Engage in political/societal debates to clarify boundaries for data usage |
- Engage in political/societal debates to improve privacy and data protection policies and to ensure accountability of those that violate these rights | |
- Consider aggregating data to avoid drawing conclusions about individuals at later stages | |
- Engage in user education | |
- Strengthen transparency about data use, data sharing and potential risks | |
- Strengthen support measures (e.g., for older individuals) | |
- Follow strict data protection regulations (e.g., only ask for thematically relevant data) | |
- Create conditions that ensure that the extent of data entries is fully understood by all individuals | |
- Ensure the voluntary nature of the data entries | |