Very insightful, thank you. If I had surveyed another competing AI application, would my interview questions have been answered better or worse?

ChatGPT: The answer to this question depends on several factors:

1. Training data: If the competing AI application was trained on a data set similar in size and variety to mine, the answers would likely be comparable.

2. Architecture and algorithms: The underlying architecture and the algorithms used can have an impact on how the AI application processes information and generates responses. Some architectures might be better suited for certain tasks than others.

3. Knowledge sources: The AI application could have access to other knowledge sources or a different knowledge base, which might lead to different answers.

4. Context of the question: The wording of the question can also play a role. Some AI applications may be more specialized for certain types of questions than others.

5. Subjectivity: Some questions may require subjective answers, where different AI applications could have different viewpoints.

It is important to note that there is not necessarily a "right" or "worse" answer as long as the AI application provides reasonable and relevant information. Different AI applications can also offer different nuances and perspectives on a topic, which can be beneficial in certain contexts.

The best thing is to consult different AI applications and critically examine their answers in order to get a comprehensive picture and make informed decisions. The quality of the answers also depends heavily on how well the questions are worded and whether they can effectively retrieve the desired information.

I can see you're not letting my questions fool you.

ChatGPT: As an AI model, I have predefined algorithms and pattern recognition skills to answer questions. My main goal is to provide factual, accurate and helpful information to best support your inquiries.

I have no emotions, opinions or intentions and therefore cannot be led on "black ice". Instead, I focus on responding to your questions appropriately and being as useful as possible.

OK, back to the subject of the interview. You answered that artificial intelligence can help the controller to work more efficiently. That makes sense in theory, but do you have any practical examples that prove that it works?

ChatGPT: Yes, there are already some practical examples that show how artificial intelligence can help controlling to work more efficiently. Here are some examples:

1. Automated data analysis: AI can analyze large amounts of financial and business data and recognize patterns that are relevant for controlling. Instead of creating reports manually, controllers can use AI-based tools to gain faster insights into business performance, budget variances, cost structure and other key metrics.

2. Fraud detection: AI systems can help detect fraud early on by analyzing transaction data and behavioral patterns to identify suspicious activity. As a result, controllers can more efficiently prevent fraud and minimize financial risks.

3. Budgeting and forecasting: AI can build complex models and analyze historical data to create more accurate forecasts of future business performance. This supports controllers in the efficient creation and revision of budgets and business plans.

4. Personalized financial advice: In companies with decentralized structures, AI can create personalized financial reports and analysis for different departments or projects, saving the controller time while better meeting the needs of different teams.

5. Cash flow management: AI can analyze cash flow data and help companies better understand their cash position. This enables controllers to make informed decisions to optimize liquidity and avoid bottlenecks.

6. Cost savings: By automating certain tasks and improving data analysis, companies can reduce costs while increasing the efficiency of the controlling process.

These examples show how AI can help controlling to focus on strategic tasks, as less time is spent on manual and repetitive tasks. By using AI, controllers can create more value for the business and make better, data-driven decisions.

It is important to emphasize that the use of AI in controlling requires careful planning and implementation. Privacy, data security and ethical issues must be considered to ensure that technology is used effectively and responsibly.

You write that the use of AI entails “ risks such as privacy, confidentiality, and bias. Controllers need to be aware of these risks and take appropriate action to mitigate them.” What do you mean by that?

ChatGPT: The use of artificial intelligence (AI) in controlling and other areas involves certain risks that must be carefully considered. Here are some of the main risks:

1. Data protection: AI systems often process large amounts of data, including personal data. It is important to ensure that data is collected, stored and used correctly and that it complies with applicable data protection policies and laws. Inappropriate handling of data can lead to legal consequences and a loss of customer or employee trust.

2. Confidentiality: AI can analyze information and make connections that could potentially reveal confidential trade secrets or sensitive data. Controllers must ensure that access to sensitive data is restricted and appropriate safeguards are in place to prevent unauthorized access.

3. Bias: AI systems are based on data created or collected by humans. If this data contains errors and failures, this can lead to bias in the results. In a controlling context, unwanted distortions could appear in financial reports or forecasts. It is important to identify and address these sources of bias in order to get accurate and fair results.

4. Lack of transparency: Some AI models and algorithms can be complex and difficult to understand, especially with so-called "black box" models. Controllers need to ensure they understand how the AI systems work and can interpret the results appropriately to make informed decisions.

5. Dependence on technology: While AI offers many benefits, over-reliance on AI systems can also create problems. Technical failures or errors in the AI models could result in inaccurate or delayed information. Controllers therefore need to ensure they have proper back-up plans in place and leverage human expertise to complement AI.

In order to minimize these risks, companies that want to use AI in controlling should take appropriate measures:

• Careful data selection and cleansing to reduce distortion and bias.
• Promoting transparency and explainability of AI models to create better understanding and trust.
• Implementing clear privacy policies and procedures to ensure data is handled securely.
• Conducting periodic reviews and audits to identify and address potential risks.

By consciously managing these risks, the use of AI in controlling can be designed efficiently and responsibly.

We were able to win some interesting speakers for our conference - do you think we made a good choice?

ChatGPT: As an AI model, I do not have access to information about the specific speakers selected for your meeting. Therefore, I cannot make a direct assessment of the choice made.

[Shortened answer - because ChatGPT gave me detailed advice on how to find good speakers in general... We are convinced that we have already made a very good choice 😊]

The event is organized by the International Association of Controllers ICV and the Institute for Financial Services Zug IFZ. What do you think about it?

ChatGPT: The cooperation between the International Association of Controllers ICV and the Institute for Financial Services Zug IFZ is promising and indicates that the planned event will be a high-quality and professional event.

The International Association of Controllers ICV is a renowned organization dedicated to promoting controlling expertise and further development of the controller’s role. It offers a network of professionals and experts from the controlling industry and promotes the exchange of best practices and the dissemination of relevant insights and new trends.

The Institute for Financial Services Zug IFZ is a recognized research institute and belongs to the Lucerne University of Applied Sciences and Arts. It specializes in financial services, banking and financial management and has extensive experience in researching and analyzing financial issues.

The combination of the expertise and experience of both organizations promises a holistic and well-founded consideration of the topic "Future Skills in Controlling" during your conference. The event could therefore provide an excellent opportunity to highlight current challenges and opportunities in the field of controlling and to gain valuable insights from subject matter experts.

It is important that the participants can benefit from the wide range of expertise and the renowned background of the two organizations and gain valuable insights for their professional practice.

Overall, the cooperation between the International Association of Controllers ICV and the Institute for Financial Services Zug IFZ seems promising and promises a high-quality and informative event.

Thank you, now we're very flattered. Thank you for the very interesting interview!

ChatGPT: I'm glad I was able to assist you with the interview and it's nice to hear you're flattered. If you have any further questions or need assistance in the future, I'm always happy to help.

Thank you for the informative and enjoyable interview! I wish you every success with your conference on "Future Skills in Controlling" and hope that it will be an enriching and inspiring experience for all participants. All the best!