Critically reflective AI compass

• Sensitive data includes, e.g., personal data that can identify an individual; (unpublished) research data; confidential information; meeting minutes; sensitive personal information such as health records or financial records.
• Such data should not be entered into AI systems; if this is necessary nonetheless, consent of the people affected must be obtained or the data must be rendered anonymous.
• Use data economically and minimise its use.
• Follow the General Data Protection Regulation (GDPR) and other relevant data protection regulations.

• Relevant rights include copyrights as well as personal and intellectual property rights.
• Respect copyrights when using and creating AI-generated content.
• Avoid using copyrighted material without authorisation.
• Ensure that all data and materials used have been acquired legally and cited correctly.
• Protect your own intellectual property by clearly documenting and labelling your work.
• Be aware that the training of AI algorithms may violate existing copyrights and intellectual property rights. AI models are often trained using large data sets which may contain copyrighted content. Make sure that the training data has been acquired legally and does not violate any third-party rights as far as possible.

• Be aware of potential bias that can result from the use of AI tools. Always analyse results critically.
• Understand that your input can be processed by AI systems and possibly used for training purposes.
• Pay attention to what data you enter and what consequences this could have.
• Review results and underlying data on a regular basis in order to recognise and correct possible biases and errors.
• Scrutinise the algorithms and methods used in AI systems and ensure transparency and traceability in decision-making processes.

Transparency and accountability are essential when using AI.

• Clearly disclose which parts of the work were created with the help of AI and which were produced independently.
• Ensure that the final product remains under your responsibility and that the use of AI is traceable.
• Document and reflect transparently on the methods and results to ensure sound academic, artistic, and creative work.
• Regularly review and evaluate the methods and results to identify AI-generated errors and biases in the AI. This is part of the critical reflection that is always expected of students at the University of the Arts.
• Ensure that the use of AI is in accordance with the rules of good scientific, creative, and artistic practice and complies with the guidelines of the relevant course or the rules for theses.

AI can be used in various ways: as a support tool or through the direct use of AI-generated content in texts, images, translations, audiovisual projects, and other artistic fields. Every use of AI must be documented in an accompanying protocol. Protocols should clearly and explicitly document and explain the creation and decision-making processes, as well as the results, in which AI is involved. It should also be noted whether AI was used as a result or as a tool (for research).

• Protocols are important to ensure the transparency and traceability of AI use. They should include:
  Example of protocol content
  A protocol should contain the following points to make the use of generative AI transparent and traceable:
• Name of the person who used the AI.
• Date or time period: The period during which the AI was used.
• Your own concept: Describe the concept of your work.
• Description of the prompts: Which prompts were provided to the AI tool to guide and achieve the result?
• Description of the use of AI:
  Whether the AI was used as a tool or to create content.
  Specification of use: How and why the AI was used.
  Justification for the use of AI: Why AI was chosen for this project.
• Chronological development: Documentation of the development of your concept in individual steps (it does not have to

• Ensure that your work reflects your own creative and intellectual effort. Unless otherwise explicitly agreed, AI tools should be used as a support and must not replace your own skills and thought processes. It must be clearly evident which portion of the work was produced by the students themselves.
• Ensure that your work can be recognized as your own by making sure that it reflects your own creative and intellectual effort and that AI is not misused as a substitute for your own abilities.

Be aware that future software may be able to identify even older AI-generated work. This means that the origin and integrity of your work can be verified even in the long term. Transparent documentation and labeling are therefore essential to ensure that your decisions remain traceable in the future.

Ensure that your work is grounded in academic, creative, and artistic principles. Practice rigorous self-monitoring and critical evaluation of AI-generated content and AI tools to ensure their integrity.

• Use literature reviews and reliable sources to support and validate your work, and regularly seek feedback from your instructors, experts, and fellow students.
• Document the entire work process in detail (including the methods and materials used without AI).
• Adhere to the general guidelines for good academic, creative, and artistic work at the University of the Arts and to the requirements of your course (as communicated on ufg-online and at the beginning of the course).

Be curious and use AI to explore new creative approaches; but always remain critical of the aesthetic and artistic limitations of these technologies. Experiment with various AI tools to develop ideas and bring projects to life, while reflecting on their impact on your creative practice.

• Use AI to explore creative approaches and develop new perspectives by trying out different algorithms and techniques.
• Be aware of the limits of AI and critically reflect on its aesthetic and artistic limitations.
• Experiment with various AI tools and reflect on how they influence your creative practice, for example, by keeping a log of your experiments.

AI tends to invent facts. Therefore, you cannot rely on the accuracy of the results under any circumstances! It is the user’s responsibility to verify the content of AI-generated results. Carefully check the accuracy of AI-generated information and be aware of potential limitations and biases inherent in AI or that may arise from the use of AI tools.

Carefully verify the accuracy of information generated by AI by comparing it with reliable sources.

Be aware that AI tools and AI-generated results may contain biases, and critically reflect on potential limitations by questioning them.

Ensure the ethical and integrity-driven use of AI in your work by paying attention to the following aspects:

• Adhere to ethical standards and practices by regularly staying informed about the latest ethical guidelines from the University of the Arts and applying them.
• Ensure the integrity of your work by always working honestly and transparently and clearly documenting every step of your work.
• Ensure the security of the data you use and the AI tools you employ by complying with security standards (see Rights and Data) and regularly updating your security software.
• Observe data protection regulations and protect personal data to safeguard privacy by anonymizing or pseudonymizing personal data.

Responsibility and Reliability

Ensure that your work is reliable and responsible.

• Ensure the reliability of your results by double-checking them and having them validated by independent third parties.
• Be aware of how resource-intensive the development and use of generative AI are! Therefore, ensure sustainable use and minimize waste!
• Ensure that your work is legally compliant by adhering to all relevant laws and regulations and seeking legal advice when necessary.
• Consider the social impact of your work and act responsibly toward society by assessing the potential consequences of your work.
• Be aware of possible negative consequences and take preventive measures to avoid them.

Accountability and Transparency

Take responsibility for the content you use and ensure transparency in your creative process.

• Cite the sources of your content accurately and follow academic citation standards.
• Adhere to the principles of academic integrity and work honestly and fairly.
• Be accountable for any content you use and take responsibility for its accuracy.
• Double-check the accuracy of the information to avoid using inaccurate, misleading, or completely fabricated materials.
• Clearly explain your use of AI and ensure transparency in your creative process by documenting your methods and results in detail and making them comprehensible to others.

Clearly document and identify the use of AI tools in your work. (Protocol)

• Specify which AI tools were used and for what purpose.
• Describe how the AI tools were integrated into the creative process.
• Ensure that the role of the AI tools in the work is clearly identifiable.

Cite AI-generated content and clearly indicate which parts of your work were supported by AI. This includes the generation of ideas, text, translations, as well as design and artistic content.

• Clearly mark the sections or elements that were generated by AI.
• Cite AI-generated content by specifying that it was created by AI. This is important to ensure transparency and traceability.
• Adapt citation guidelines by describing not only the source but also the exact use and the modifications made to the AI-generated content. This helps clarify the original generative processes and your role in the subsequent editing.

Transparency

Ensure that the use of AI in your work is clear and traceable.

• Document all steps performed using AI tools in detail via a log.
• Explain the decision-making processes and methods that led to the use of AI.
• Ensure that the documentation is comprehensible to third parties.

Good scientific, creative, and artistic practice

Adhere to the standards of good scientific, design, and artistic practice, including when using AI.

• Follow the University of the Arts’ ethical guidelines and standards.
• Ensure the integrity and quality of your work through careful documentation and critical reflection.
• Regularly review your methods and results for accuracy and fairness.

Accountability and transparency are crucial for ensuring traceability and accountability.

• Take responsibility for the accuracy and integrity of AI-generated content. Be aware that you are liable for the accuracy and reliability of AI-generated content.
• Be aware of the consequences that may arise from the use of AI. This applies to both legal and ethical consequences.
• Ensure that your work is verifiable with regard to all AI tools and methods used. To this end, maintain detailed records that allow for third-party verification.
• As both a developer and a user of AI, take responsibility for the results and their implications. This includes responsibility for potentially erroneous or biased results.

Clean systems are AI systems that are based on lawfully obtained and ethically sound training data, do not process sensitive or third-party data, and take social and environmental criteria into account.

• Lawful training data: Use only AI systems whose training data comes from legitimate, legally sound sources. Ensure that no stolen or unethically obtained data has been used.
• Avoidance of Sensitive Data: Do not feed AI systems with personal or confidential information to protect the privacy and rights of third parties, as well as your own information and that entrusted to you. Avoid entering data that contains financial, health, or other sensitive information (see „Daten und Rechte“).
• Transparency and traceability: Use AI systems whose origins and datasets are transparent and traceable. Providers should disclose what data was used to train the AI and how that data was collected. It should also be transparent how and whether the AI processes your inputs and whether and where this information is stored.
• Ethical Considerations: Take ethical aspects into account when selecting and using AI systems. Ensure that the systems do not promote discrimination or bias and that they are used responsibly.
• Environmental awareness: Be aware of how resource-intensive the development and use of AI systems are for the environment! Consider the energy consumption and ecological impact of the systems.
• Social responsibility: Ensure that AI systems meet social criteria and do not have negative impacts on specific groups. Pay attention to the inclusion and diversity of the training data. Also be aware that the process of data labeling—a central step in AI development—is most often carried out by workers from the Global South, who often work under poor conditions, receive miserable pay, and face psychologically demanding circumstances!
• Inclusive and diverse training data: Whenever possible, use AI systems whose training data includes a diverse and representative selection of data to avoid a Western, white, male bias. Promote anti-racist, anti-sexist, and non-colonialist approaches in the use of AI.

Understand the basic principles and capabilities of AI tools, as well as their limitations and risks. Take advantage of the resources and support services available at the university and engage in ongoing professional development. This includes:

• Fundamentals and Applications: Learn about how AI tools work and their potential applications. Understand how these tools function and in which areas they can be applied.
• Critical evaluation: Remain critical of the promises and hype surrounding AI and evaluate its impact on your discipline. Analyze the advantages and disadvantages of using AI.
• Understand the limitations and risks of AI systems in order to use them responsibly:

1. Inaccuracy: AI systems can produce inaccurate, erroneous, and fabricated results. It is important to always question these results, compare them with reliable sources, and then evaluate them critically.
2. Human-in-the-loop and accountability: Ensure that a human is always involved in the decision-making process. Take responsibility for the content generated by AI and ensure that decisions are not made exclusively by machines.
3. Infringement of intellectual property rights: AI models can generate content that includes copyrighted material. Be careful not to infringe on the rights of third parties, and if in doubt, clarify legal issues in advance.
4. Bias and Discrimination: AI systems can amplify existing biases or produce discriminatory results. Be aware of these risks and actively work to identify and minimize biases. Implement mechanisms to identify and prevent discrimination.
5. Source transparency: Demand transparency from the AI systems you use. Ensure that you know what data was used to train the AI and how that data was collected. Transparent sources are crucial for evaluating the quality and ethics of AI results (see “Clean Systems”).

• Resources and Professional Development: Take advantage of the support and regular opportunities offered by the University of the Arts to deepen your knowledge. Participate in workshops and training sessions on the use of AI, and bring your own critical and reflective perspective to the table.
• Current Developments: Stay informed about current developments and new tools in the field of AI. Examine their social and artistic implications and critically discuss your experiences and best practices with fellow students and faculty.
• Ethical Discussions: Discuss the use of AI with your faculty and clarify ethical questions, particularly in thesis projects. Ensure that the use of AI tools in your work is ethically justifiable and appropriate.
• Critical use of AI tools: Use AI tools to support literature research, data analysis, writing processes, image editing, music composition, video production, and other artistic processes, but critically evaluate the generated results each time. Use AI to analyze complex data and verify the results for validity and reliability.
• Evaluating Information: Critically analyze the information provided by AI tools and compare it with reliable sources.
• Bias Detection: Be aware that AI systems may contain biases and perpetuate them in their results! Therefore, scrutinize every result for potential biases and their causes.
• Error detection: Regularly check the AI’s results for errors and inconsistencies and correct them as necessary.

When sharing data and assessing the consequences of AI use, consider the following aspects:

• Data sharing: Share data only with trusted parties and ensure that data protection regulations are followed. Be aware that your inputs may be processed and shared. Critically examine which third-party providers have access to the data and what risks are associated with this.
• Storage of inputs: Find out how and where your inputs are stored. Consider the implications this has for data security and privacy.
• Impact assessment: Evaluate the potential effects of your work with AI on society, the environment, and other relevant factors. Ensure that your work does not have negative consequences. Reflect on possible ethical dilemmas and the long-term consequences of using AI.

Ensure that people always retain control when using AI and that the benefits of AI are distributed equitably. This includes:

• People in Control: Ensure that people always retain control over AI systems and that decisions are not made exclusively by machines.
• Human-in-the-loop: Integrate human feedback and oversight into the AI-supported process. Ensure that human supervision is present for critical decisions.
• Shared benefits: Ensure that the benefits of AI are distributed equitably and do not disproportionately benefit specific groups. Advocate for equitable access to the benefits of AI.

Fairness, Bias und Diskriminierung

Arbeiten Sie daran, Fairness zu gewährleisten und Bias sowie Diskriminierung zu vermeiden. Dies umfasst:

• Fairness: Stellen Sie sicher, dass die von KI generierten Ergebnisse fair und gerecht sind. Überprüfen Sie regelmäßig, ob die KI-Systeme fair und ausgewogen arbeiten.
• Bias: Seien Sie sich der möglichen Verzerrungen bewusst und arbeiten Sie daran, diese zu minimieren. Entwickeln Sie Methoden, um Bias zu erkennen und zu korrigieren.
• Diskriminierung: Achten Sie darauf, dass Ihre Arbeit mit KI keine diskriminierenden Auswirkungen hat. Implementieren Sie Mechanismen zur Identifizierung und Vermeidung von Diskriminierung.

Consider the impact of AI on the environment and social factors. This includes:

• Environmental Impact: Assess the environmental consequences of your work with AI and strive for sustainable solutions. Consider how energy consumption and resource use can be minimized.
• Social Factors: Consider the social impact of your work and ensure that it is positive and equitable. Ensure that your work contributes to the promotion of social justice.

Prosperity and the Common Good

Strive to ensure that your work with AI contributes to general prosperity and the common good. This includes:

• Prosperity: Work toward ensuring that your work with AI contributes to improving quality of life and general prosperity. Consider how your work can support positive social change.
• Public good: Ensure that your work benefits society as a whole. Advocate for projects that promote the public good and create social value.