How we talk to AI Bots, EU Directive NIS 2: A Race against Time, AI Creativity vs. Copyright Law, Smart Cities, Data Quality as Challenge
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In this issue of our i40 - the future skills newsletter, we address the art of communicating with AI bots, the race against time with regard to the EU NIS 2 directive, legal challenges with AI-generated content, innovative smart cities for more sustainability and the obstacles that companies experience due to insufficient data quality when implementing AI.?
The art of AI communication: between being on first-name-terms, praise and the power of spelling?
Almost all users are on first-name terms with AI — 99%, to be precise. Only a tiny proportion remain formal and address the bot as “you”. But it's the tone that makes the music: according to a survey by the digital association Bitkom , two thirds of respondents (66%) pay attention to correct spelling, with older users (aged 50 and over) attaching particular importance to this.??
Younger generations, on the other hand, often take a more relaxed approach to the wording. It is also interesting to note that only 45% of users formulate their requests with a polite “please”, and only 29% regularly thank the AI. But why is politeness even relevant when communicating with AI if the machine has no emotions???
Structured requests can actually lead to better results. This is because AI models such as ChatGPT or Google Gemini have also been trained with natural, human language - polite, well-thought-out input can therefore provide accurate and helpful answers. Nevertheless, the survey also shows another side to communication: 6 percent of respondents have already insulted their AI bot, with men (9 percent) being more likely to be offensive than women (3 percent). Interestingly, 13% of users have also praised their AI at some point - praise therefore also seems to be part of human interaction with AI, albeit rarely.??
To get the best out of an interaction with an AI bot, there are a few tips to keep in mind:??
Precise and clear requests: Make your questions or tasks as specific as possible. The more precise the instruction, the better the result.??
Politeness and structure: A friendly and structured formulation helps the AI to better understand your request. Phrases such as “please” and “thank you” are not necessary, but they can have a positive influence on the quality of the response.?
Pay attention to spelling: Even though AI can often cope with imprecise wording, correct spelling and punctuation improves the precision of responses.??
Give feedback: If the answer is not satisfactory, try using clearer or alternative wording. This not only helps you, but also the AI to better understand what you need.??
Targeted training and webinars help to further optimize communication with AI. You can find more information here: AI training and webinar ?
NIS 2 - The countdown is on??
NIS 2 is currently giving cyber security managers sleepless nights.??
In Germany alone, around 30,000 companies will have to meet the requirements of the second EU directive on network and information security (NIS 2 directive), even though they were spared by NIS 1. This means that those responsible will have to take a close look at their IT infrastructure and close any gaps they find. They don't have much time left to do this.??
At the beginning of October, the German government presented the draft law to implement the NIS 2 directive . NIS 2 is due to come into force from March 2025. Companies that fail to comply with the law can then be prosecuted. Whether there will be enough time seems questionable.??
A study by Plusnet on the implementation of NIS 2 in Germany shows a considerable discrepancy between the target and actual situation. According to their own statements, 2 out of 3 companies do not fulfill the technical security measures. 58 percent of companies do not have any mandatory security training.??
Interestingly, companies are aware of the impending danger. More than half of the companies surveyed have been attacked themselves in the last 12 months and expect attacks to increase rather than decrease.??
This discrepancy is easy to explain: Cyber security costs time and resources, without the customer being willing to pay more for it. Converting your own IT infrastructure is a lengthy project that has to be carried out step by step. Companies must carefully weigh up the risks against the costs of a loss event. In many cases, it is cheaper for companies to accept the damage caused rather than convert their own infrastructure.??
EU member states are therefore obliged to ensure that their national laws provide for fines with a maximum amount of at least 10 million euros or at least 2 percent of the company's turnover. How high the fines will be in practice will become clear from March 2025.??
Does commercial AI creativity need different contracts???
European copyright law is inextricably linked to the idea of personal intellectual creation - something that is not the case with generative AI systems. Nevertheless, companies want to be able to use AI-generated content in a legally secure manner.??
What is known, however, is that traditional contracts based on copyright protection are not applicable here. They were developed for works that originate from human creators. In the case of AI-supported content, whose creation process is based on algorithms and not on human creativity, such requirements are generally lacking. Companies working with AI-generated content must therefore revise existing contractual models.??
AI-generated content is created by training on extensive data sets, which can lead to unintended similarities with existing works under certain circumstances.?
In order to minimize uncertainties, it is crucial to create transparency: Clear information about the AI-generated works and a precise distribution of rights are of central importance here.?A carefully drafted license agreement that clearly regulates these aspects is essential to ensure long-term security and reliability in the use of AI content.??
If you would like to learn more about the important legal aspects of contracts for commercial AI creativity, please see the article linked below.??
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Intelligent solutions conserve resources: digital innovations in smart cities??
Smart cities use digital technologies and data to make the lives of citizens more efficient and livable. In Hesse, for example, many cities have already started to focus on data-based innovations. It is not only administrative processes that play a role here, but above all advanced infrastructures that are continuously optimized through the collection and evaluation of data.??
A striking example of the use of data is public transport in Fulda, where sensors in buses provide real-time information on capacity utilization and position. This data enables transport planners to dynamically adapt operations to actual demand and offer passengers reliable planning of their journeys. However, the use of data in smart cities not only offers benefits to citizens, but also opens up significant opportunities for urban infrastructures and the economy.?
By continuously recording and analyzing real-time data, processes can be adapted flexibly and precisely, leading to a significant increase in efficiency in various areas. For companies, this primarily means an optimized use of resources, shorter response times and leaner processes overall. A key argument for data-driven smart city solutions is improved decision-making. Companies benefit from a detailed overview of urban operations, enabling them to make strategic decisions based on accurate and up-to-date information.???
This is particularly relevant for the design of future-oriented and sustainable business models that rely on technological innovations and resource-efficient solutions.???
The aspect of sustainability is also playing an increasingly important role. Intelligent systems help to use valuable resources such as energy and water in a targeted and economical manner. This is not only important from an ecological point of view, but also contributes directly to cost reduction, which has a positive impact on municipal finances. A good example of this are smart grids and automated irrigation systems that use resources exactly when they are needed, thus avoiding unnecessary waste.?
Security and resilience are also key benefits that should be considered. Data makes it possible to identify potential dangers at an early stage and take preventive measures. This applies not only to traffic or public safety, but also to the prediction and management of natural events such as floods or heatwaves. Companies that have access to such data can adapt their business processes and prepare for unforeseeable events. In the long term, data-based smart cities contribute to a better quality of life and promote sustainable urban growth. They combine technological innovation with social and environmental responsibility, which is essential for future-proof development.??
Source: https://www.heise.de/news/Daten-nutzen-fuer-Lebensqualitaet-Smart-Cities-in-Hessen-9838832.html ??
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Data quality and governance as an obstacle to AI adoption ?
A study by data integrity specialist Precisely clearly shows that while 60 percent of companies recognize the importance of AI for their data programs, only 12 percent have data that is qualitative and accessible enough to use AI effectively. ?
This has far-reaching consequences: Decisions based on unreliable or incomplete data can lead to faulty conclusions and suboptimal business decisions. This is a huge obstacle for companies that want to be successful in digital transformation and automation.?
Another problem is the lack of data governance. 62% of the companies surveyed named this as the biggest obstacle to implementing AI projects. Without a clear governance structure, data is often poorly organized, inconsistent or incomplete. Data without solid governance is difficult to scale and makes it difficult to establish standardized processes. This prevents AI models from obtaining the data they need to deliver precise and meaningful analyses. ?
The situation is further exacerbated by the lack of specialists. 60 percent of companies stated that a lack of skills and training in the field of AI is a major challenge. Companies are therefore forced to invest in the further training of their employees in order to meet the requirements of AI implementation. ?
However, there is a ray of hope in the increasing acceptance of data governance. More than half of companies have now established a governance program, leading to improved data quality processes. These programs help companies to structure their data in order to create the basis for successful AI applications. For companies, this means that investment in data quality and governance is essential to benefit from AI in the long term. Those who do not overcome these hurdles run the risk of being left behind by the competition.?
New episodes Digikompetenz Podcast in November 2024
We are looking forward to the new episodes in November with:?
#168 Bob Wise served in the West Virginia State Senate and later represented West Virginia in the U.S. House of Representatives for 18 years before becoming the 33rd Governor of West Virginia from 2001 to 2005. Bob served as President of the Alliance for Excellent Education (All4Ed), a Washington, DC–based national leader in advocating the policies and practices necessary for secondary school students to be ready for postsecondary education and careers. He is the Co-Founder of the Global Science of Learning Education Network. Additionally, he is on the Advisory Board of the University of California, San Francisco (UCSF) Dyslexia Center.?
#169 Felix von Kunhardt is Head of Emerging Products at G-P with extensive experience in e-commerce, digital experience analytics and social. He has held leadership positions at eBay, AOL and Decibel. At AOL he was Executive Head of Product Management and led the German product management team at eBay before expanding the brand store concept across Europe as Director EU Client Services. He was later CPO at Decibel, where he promoted product innovation and digital customer experiences. Felix is also co-founder of several start-ups such as the social commerce platform Sellaround and worked as CPO at bellicon USA.?
More than 160 episodes of our DIGIKOMPETENZ PODCAST are already online: with exciting and inspiring guests such as Richard David Precht, Ranga Yogeshwar, the Parliamentary State Secretary at the Federal Ministry for Digital and Transport, Daniela Kluckert, Spiegel reporter Thomas Schulz, Managing Director of Süddeutsche Zeitung Digitale Medien, Johannes Hauner, CEO of the cult business magazine brand eins, Holger Volland, those who completed the Beethoven symphony with AI, Dr. Matthias R?der, Walter Werzowa, Seda R?der, CEO of DB Cargo, Dr. Sigrid Nikutta, Head of Dealer Development, Audi, Heiko Schmidt, Head of Future of Work Project Harvard Business School, Professor Joseph Fuller, LEGO Talent Leadership & Organization Development Johannes Lystb?k and David T?ttrup, blockchain specialist at RMIT Vietnam, Dr. Binh Nguyen Thanh, US neuroscientist and AI expert, Dr. Vivienne Ming, Vice President and Managing Director, Adobe Central Europe, Christoph Kull, Head of Watson, Data Science & Artificial Intelligence, IBM, Dr. Wolfgang Hildesheim, Divisional Board Member for Corporate Clients at Commerzbank Guido Gro?, Mina Saidze, Thought Leader in Data and AI, author FairTech, Nina Michahelles, Director Large Customer Sales, Google, Jason Feifer, Editor in Chief of Entrepreneur magazine in USA, Stephan Scheuer, Silicon Valley Correspondent at Handelsblatt, Christian Reincke, Head of People Development at EDAG, Dr. Claudia Viehweger, Chief People & Sustainability Officer at Scout 24 Group, Google’s first and former Chief Innovation Evangelist and Thought Leader Dr. Frederik G. Pferdt, VP CNN and Editor-in-Chief CNN Arabic Dr. Caroline Faraj, and many, many more.?
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