Was ist das eigentlich? Cyberrisiken verständlich erklärt
Es wird viel über Cyberrisiken gesprochen. Oftmals fehlt aber das grundsätzliche Verständnis, was Cyberrisiken überhaupt sind. Ohne diese zu verstehen, lässt sich aber auch kein Versicherungsschutz gestalten.
Beinahe alle Aktivitäten des täglichen Lebens können heute über das Internet abgewickelt werden. Online-Shopping und Online-Banking sind im Alltag angekommen. Diese Entwicklung trifft längst nicht nur auf Privatleute, sondern auch auf Firmen zu. Das Schlagwort Industrie 4.0 verheißt bereits eine zunehmende Vernetzung diverser geschäftlicher Vorgänge über das Internet.
Anbieter von Cyberversicherungen für kleinere und mittelständische Unternehmen (KMU) haben Versicherungen die Erfahrung gemacht, dass trotz dieser eindeutigen Entwicklung Cyberrisiken immer noch unterschätzt werden, da sie als etwas Abstraktes wahrgenommen werden. Für KMU kann dies ein gefährlicher Trugschluss sein, da gerade hier Cyberattacken existenzbedrohende Ausmaße annehmen können. So wird noch häufig gefragt, was Cyberrisiken eigentlich sind. Diese Frage ist mehr als verständlich, denn ohne (Cyber-)Risiken bestünde auch kein Bedarf für eine (Cyber-)Versicherung.
Wo erhalte ich vollständige Informationen über DP-900?
Nachfolgend finden Sie alle Details zu Übungstests, Dumps und aktuellen Fragen der DP-900: Microsoft Azure Data Fundamentals Prüfung.
2023 Updated Actual DP-900 questions as experienced in Test Center
Aktuelle DP-900 Fragen aus echten Tests von Killexams.com - easy finanz | easyfinanz
![]() Microsoft DP-900 : Microsoft Azure Data Fundamentals ACTUAL EXAM QUESTIONSExam Dumps Organized by Richard |
Latest 2023 Updated Microsoft Microsoft Azure Data Fundamentals Syllabus
DP-900 ACTUAL EXAM QUESTIONS / Braindumps contains genuine test Questions
Practice Tests and Free VCE Software - Questions Updated on Daily Basis
Big Discount / Cheapest price & 100% Pass Guarantee
DP-900 Test Center Questions : Download 100% Free DP-900 ACTUAL EXAM QUESTIONS (PDF and VCE)
Exam Number : DP-900
Exam Name : Microsoft Azure Data Fundamentals
Vendor Name : Microsoft
Update : Click Here to Check Latest Update
Question Bank : Check Questions
Download free DP-900 PDF Download with PDF Braindumps and Exam Questions
Killexams.com recommends that you try its free DP-900 test. Its DP-900 Practice Questions is really easy to use on Mac, Windows, Android, and Linux. You can print DP-900 Study Guide and make your own book to study as you travel. Once you feel that you have enough knowledge, take a practice questions with the VCE test simulator. Killexams.com gives you six months of free updates of DP-900 Microsoft Azure Data Fundamentals test questions.
There are numerous online Latest Questions providers, but most of them are reselling outdated dumps. To ensure success in your DP-900 exam, it's important to find a reliable and trustworthy PDF Braindumps provider. You can either study on your own or trust in killexams.com. However, be mindful that your research shouldn't end up being a waste of time and money. They recommend that you go directly to killexams.com and obtain the 100% free Actual Questions trial questions to assess their quality. If you're satisfied, register and get a 3-month account to obtain the latest and valid Exam dumps that includes real test Questions and Answers at great discounts. Additionally, you should also get the DP-900 VCE test simulator for practice.
We have received positive feedback from many individuals who have passed their DP-900 test using their Exam dumps. They have landed great positions in their respective companies, and it's a fact that using their DP-900 Exam dumps, they have experienced an improvement in their understanding of the subject matter. They can operate in real environments as professionals. Their focus is not just on passing the DP-900 test with braindumps, but also on improving knowledge of DP-900 objectives and subjects. This way, people become effective in their respective industries.

DP-900 test Format | DP-900 Course Contents | DP-900 Course Outline | DP-900 test Syllabus | DP-900 test Objectives
Test Detail:
The Microsoft DP-900 exam, also known as Microsoft Azure Data Fundamentals, is designed to assess the foundational knowledge and understanding of data concepts and core services on the Microsoft Azure platform. This certification is suitable for individuals who want to start a career in data-related roles or who need to work with data in their current roles.
Course Outline:
The course for Microsoft Azure Data Fundamentals covers various fundamental concepts and services related to data management and processing on the Azure platform. The following is a general outline of the key areas covered:
1. Introduction to Data Concepts:
- Understanding core data concepts, such as relational and non-relational data, structured and unstructured data, big data, and batch/streaming data.
- Exploring data processing and analytics techniques.
2. Core Azure Data Services:
- Overview of Azure data services, including Azure SQL Database, Azure Cosmos DB, Azure Data Lake Storage, and Azure Synapse Analytics.
- Introduction to Azure Data Factory and Azure Databricks.
3. Relational Data in Azure:
- Understanding Azure SQL Database and its features, such as deployment options, security, scalability, and performance.
- Exploring Azure Database for MySQL and Azure Database for PostgreSQL.
4. Non-Relational Data in Azure:
- Overview of Azure Cosmos DB and its features, including global distribution, scalability, and consistency models.
- Introduction to Azure Table Storage, Azure Blob Storage, and Azure Queue Storage.
5. Data Integration and Orchestration:
- Introduction to Azure Data Factory and its capabilities for data integration and orchestration.
- Overview of data ingestion and transformation using Azure Databricks.
6. Data Analytics and Visualization:
- Introduction to Azure Synapse Analytics (formerly SQL Data Warehouse) and its capabilities for data warehousing and analytics.
- Exploring Azure HDInsight and its support for big data processing.
- Overview of Power BI and its role in data visualization and reporting.
Exam Objectives:
The Microsoft DP-900 test focuses on evaluating the candidate's knowledge and understanding of the following key areas:
1. Understand Core Data Concepts
2. Describe Core Azure Data Services
3. Describe how to work with Relational Data on Azure
4. Describe how to work with Non-Relational Data on Azure
5. Describe an Analytics workload on Azure
Exam Syllabus:
The test syllabus for Microsoft Azure Data Fundamentals provides a detailed breakdown of the Topics covered in each test objective. It includes sub-topics, concepts, and specific tasks that candidates should be familiar with. The syllabus may cover the following areas:
- Data types and formats
- Azure SQL Database deployment models and security
- Azure Cosmos DB consistency models
- Azure Data Lake Storage and Azure Synapse Analytics concepts
- Azure Data Factory data integration and orchestration
- Azure Databricks for data ingestion and transformation
- Power BI data visualization and reporting
Killexams Review | Reputation | Testimonials | Feedback
Happy to hear that LaACTUAL EXAM QUESTIONS of DP-900 test are available here.
Selecting the best test material for the DP-900 certification test can be challenging. I lacked faith in myself and thought I wouldn't have enough knowledge to get into my desired university. killexams.com came into the picture and changed my mindset. Their study material allowed me to fully prepare for the exam, and I passed with their help. Thank you, killexams.com.
Located an accurate source for genuine DP-900 Questions.
I spent enough time studying the material and passed the DP-900 test with good marks. Although these materials are brain dumps based on the genuine test material, I do not understand people who complain about the DP-900 questions being different. Although not all questions were identical to the exam, the Topics and general approach were correct. So, if you study hard enough, you will do just fine.
Making ready DP-900 test with Questions and Answers is count number latest some hours now.
Passing the DP-900 test was a difficult task for me, but killexams.com helped me gain composure and prepare myself for the test using their DP-900 braindumps. The DP-900 test simulator was beneficial, and I was able to pass the exam, which helped me get promoted in my organization.
It is extraordinary! I got dumps updated DP-900 exam.
I decided to take the DP-900 course from killexams.com, as it was the most comprehensive option available and ultimately helped me score 90% on my DP-900 exam. I was thrilled with the way the material was presented, and the assistance provided by killexams.com made the experience much smoother. Thanks to killexams.com, I have been able to succeed in my professional career.
Great experience with DP-900 Questions and Answers, pass with high score.
There are not many DP-900 test materials available, so I bought the DP-900 Questions and Answers in advance. Honestly, it won my heart with the way the information was prepared. The maximum questions I saw on the test were exactly what was provided by killexams.com. I am relieved to have passed the DP-900 exam.
Microsoft Data Practice Test
Microsoft attacked over ‘grossly irresponsible’ security practiceTenable’s CEO and former national cyber security director to the George W Bush administration, Amit Yoran, has hit out at Microsoft and accused the software giant of deliberately putting its customers’ security at risk by keeping them in the dark over the risks and vulnerabilities they face. Yoran launched his attack after Tenable revealed the existence of a zero-day vulnerability in Microsoft Azure that, left unpatched, would enable limited, unauthorised access to cross-tenant applications and sensitive details – including, though not limited to, authentication secrets. He said Tenable customers – including an unnamed retail bank – are at this moment vulnerable to it. He said Tenable had taken this issue to Microsoft at the end of March, but it had taken over three months for Redmond to issue a fix that turned out to be incomplete, and it would take until the end of September for the revised patch to be issued. “Did Microsoft quickly fix the issue that could effectively lead to the breach of multiple customers’ networks and services? Of course not. They took more than 90 days to implement a partial fix – and only for new applications loaded in the service,” said Yoran. “That means that as of today, the bank … is still vulnerable, more than 120 days since they reported the issue, as are all of the other organisations that had launched the service prior to the fix. And, to the best of their knowledge, they still have no idea they are at risk and therefore can’t make an informed decision about compensating controls and other risk mitigating actions. “Microsoft claims that they will fix the issue by the end of September, four months after they notified them. That’s grossly irresponsible, if not blatantly negligent. They know about the issue, Microsoft knows about the issue, and hopefully threat actors don’t,” he said. Yoran said the so-called shared responsibility model of cyber security espoused by public cloud providers, including Microsoft, was irretrievably broken if a provider fails to notify users of issues as they arise and apply fixes openly. He argued that Microsoft was quick to ask for its users’ trust and confidence, but in return they get “very little transparency and a culture of toxic obfuscation”. “How can a CISO, board of directors or executive team believe that Microsoft will do the right thing given the fact patterns and current behaviours? Microsoft’s track record puts us all at risk. And it’s even worse than they thought,” said Yoran. “Microsoft’s lack of transparency applies to breaches, irresponsible security practices and to vulnerabilities, all of which expose their customers to risks they are deliberately kept in the dark about,” he added. A Microsoft spokesperson said: “We appreciate the collaboration with the security community to responsibly disclose product issues. They follow an extensive process involving a thorough investigation, update development for all versions of affected products, and compatibility testing among other operating systems and applications. “Microsoft’s lack of transparency applies to breaches, irresponsible security practices and to vulnerabilities, all of which expose their customers to risks they are deliberately kept in the dark about” Amit Yoran, Tenable “Ultimately, developing a security update is a delicate balance between timeliness and quality, while ensuring maximised customer protection with minimised customer disruption,” they said. Computer Weekly understands that the initial fix issued by Microsoft did mitigate the impact of the vulnerability for the vast majority of Azure users, and that the issue has since been fully addressed for all customers who should need to take no further action. Questions to be answeredYoran’s diatribe comes as Microsoft faces pressure in the US over its 13 July disclosure that an advanced persistent threat (APT) actor, tracked as Storm-0558 and backed by the Chinese government, had hacked into email accounts at multiple US government agencies using forged authentication tokens via an acquired Microsoft account consumer signing key. Among those understood to have had their email accounts compromised were Gina Raimondo, the US secretary of commerce, and Nicholas Burns, the US ambassador to China. At the time, Microsoft took the unusual step of issuing something of a mea culpa, as executive vice-president of security Charlie Bell put it, “the accountability starts right here at Microsoft”. The attack has understandably not gone over well in Washington DC, and later in July, a group of cross-party US senators, including Tim Kaine, who was Hilary Clinton’s running mate in the hacking-affected 2016 presidential election, wrote to US state department CIO Kelly Fletcher to demand more information on the circumstances surrounding it and establish what actually happened. Separately, Oregon senator Ron Wyden has written to attorney general Merrick Garland, Federal Trade Commission (FTC) chair Lina Khan, and CISA director Jen Easterly to request the government “take action to hold Microsoft responsible for its negligent security practices, which enabled a successful Chinese espionage campaign against the United States government”. AI in EducationIn Neal Stephenson’s 1995 science fiction novel, The Diamond Age, readers meet Nell, a young girl who comes into possession of a highly advanced book, The Young Lady’s Illustrated Primer. The book is not the usual static collection of texts and images but a deeply immersive tool that can converse with the reader, answer questions, and personalize its content, all in service of educating and motivating a young girl to be a strong, independent individual. Such a device, even after the introduction of the Internet and tablet computers, has remained in the realm of science fiction—until now. Artificial intelligence, or AI, took a giant leap forward with the introduction in November 2022 of ChatGPT, an AI technology capable of producing remarkably creative responses and sophisticated analysis through human-like dialogue. It has triggered a wave of innovation, some of which suggests they might be on the brink of an era of interactive, super-intelligent tools not unlike the book Stephenson dreamed up for Nell. Sundar Pichai, Google’s CEO, calls artificial intelligence “more profound than fire or electricity or anything they have done in the past.” Reid Hoffman, the founder of LinkedIn and current partner at Greylock Partners, says, “The power to make positive change in the world is about to get the biggest boost it’s ever had.” And Bill Gates has said that “this new wave of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone.” Over the last year, developers have released a dizzying array of AI tools that can generate text, images, music, and video with no need for complicated coding but simply in response to instructions given in natural language. These technologies are rapidly improving, and developers are introducing capabilities that would have been considered science fiction just a few years ago. AI is also raising pressing ethical questions around bias, appropriate use, and plagiarism. In the realm of education, this technology will influence how students learn, how teachers work, and ultimately how they structure their education system. Some educators and leaders look forward to these changes with great enthusiasm. Sal Kahn, founder of Khan Academy, went so far as to say in a TED talk that AI has the potential to effect “probably the biggest positive transformation that education has ever seen.” But others warn that AI will enable the spread of misinformation, facilitate cheating in school and college, kill whatever vestiges of individual privacy remain, and cause massive job loss. The challenge is to harness the positive potential while avoiding or mitigating the harm. What Is Generative AI? Artificial intelligence is a branch of computer science that focuses on creating software capable of mimicking behaviors and processes they would consider “intelligent” if exhibited by humans, including reasoning, learning, problem-solving, and exercising creativity. AI systems can be applied to an extensive range of tasks, including language translation, image recognition, navigating autonomous vehicles, detecting and treating cancer, and, in the case of generative AI, producing content and knowledge rather than simply searching for and retrieving it. “Foundation models” in generative AI are systems trained on a large dataset to learn a broad base of knowledge that can then be adapted to a range of different, more specific purposes. This learning method is self-supervised, meaning the model learns by finding patterns and relationships in the data it is trained on. Large Language Models (LLMs) are foundation models that have been trained on a vast amount of text data. For example, the training data for OpenAI’s GPT model consisted of web content, books, Wikipedia articles, news articles, social media posts, code snippets, and more. OpenAI’s GPT-3 models underwent training on a staggering 300 billion “tokens” or word pieces, using more than 175 billion parameters to shape the model’s behavior—nearly 100 times more data than the company’s GPT-2 model had. By doing this analysis across billions of sentences, LLM models develop a statistical understanding of language: how words and phrases are usually combined, what Topics are typically discussed together, and what tone or style is appropriate in different contexts. That allows it to generate human-like text and perform a wide range of tasks, such as writing articles, answering questions, or analyzing unstructured data. LLMs include OpenAI’s GPT-4, Google’s PaLM, and Meta’s LLaMA. These LLMs serve as “foundations” for AI applications. ChatGPT is built on GPT-3.5 and GPT-4, while Bard uses Google’s Pathways Language Model 2 (PaLM 2) as its foundation. Some of the best-known applications are: ChatGPT 3.5. The free version of ChatGPT released by OpenAI in November 2022. It was trained on data only up to 2021, and while it is very fast, it is prone to inaccuracies. ChatGPT 4.0. The latest version of ChatGPT, which is more powerful and accurate than ChatGPT 3.5 but also slower, and it requires a paid account. It also has extended capabilities through plug-ins that supply it the ability to interface with content from websites, perform more sophisticated mathematical functions, and access other services. A new Code Interpreter feature gives ChatGPT the ability to analyze data, create charts, solve math problems, edit files, and even develop hypotheses to explain data trends. Microsoft Bing Chat. An iteration of Microsoft’s Bing search engine that is enhanced with OpenAI’s ChatGPT technology. It can browse websites and offers source citations with its results. Google Bard. Google’s AI generates text, translates languages, writes different kinds of creative content, and writes and debugs code in more than 20 different programming languages. The tone and style of Bard’s replies can be finetuned to be simple, long, short, professional, or casual. Bard also leverages Google Lens to analyze images uploaded with prompts. Anthropic Claude 2. A chatbot that can generate text, summarize content, and perform other tasks, Claude 2 can analyze texts of roughly 75,000 words—about the length of The Great Gatsby—and generate responses of more than 3,000 words. The model was built using a set of principles that serve as a sort of “constitution” for AI systems, with the aim of making them more helpful, honest, and harmless. These AI systems have been improving at a remarkable pace, including in how well they perform on exams of human knowledge. OpenAI’s GPT-3.5, which was released in March 2022, only managed to score in the 10th percentile on the bar exam, but GPT-4.0, introduced a year later, made a significant leap, scoring in the 90th percentile. What makes these feats especially impressive is that OpenAI did not specifically train the system to take these exams; the AI was able to come up with the correct answers on its own. Similarly, Google’s medical AI model substantially improved its performance on a U.S. Medical Licensing test practice test, with its accuracy rate jumping to 85 percent in March 2021 from 33 percent in December 2020. These two examples prompt one to ask: if AI continues to Excellerate so rapidly, what will these systems be able to achieve in the next few years? What’s more, new studies challenge the assumption that AI-generated responses are stale or sterile. In the case of Google’s AI model, physicians preferred the AI’s long-form answers to those written by their fellow doctors, and nonmedical study participants rated the AI answers as more helpful. Another study found that participants preferred a medical chatbot’s responses over those of a physician and rated them significantly higher, not just for quality but also for empathy. What will happen when “empathetic” AI is used in education? Other studies have looked at the reasoning capabilities of these models. Microsoft researchers suggest that newer systems “exhibit more general intelligence than previous AI models” and are coming “strikingly close to human-level performance.” While some observers question those conclusions, the AI systems display an increasing ability to generate coherent and contextually appropriate responses, make connections between different pieces of information, and engage in reasoning processes such as inference, deduction, and analogy. Despite their prodigious capabilities, these systems are not without flaws. At times, they churn out information that might sound convincing but is irrelevant, illogical, or entirely false—an anomaly known as “hallucination.” The execution of certain mathematical operations presents another area of difficulty for AI. And while these systems can generate well-crafted and realistic text, understanding why the model made specific decisions or predictions can be challenging. The Importance of Well-Designed Prompts Using generative AI systems such as ChatGPT, Bard, and Claude 2 is relatively simple. One has only to type in a request or a task (called a prompt), and the AI generates a response. Properly constructed prompts are essential for getting useful results from generative AI tools. You can ask generative AI to analyze text, find patterns in data, compare opposing arguments, and summarize an article in different ways (see sidebar for examples of AI prompts). One challenge is that, after using search engines for years, people have been preconditioned to phrase questions in a certain way. A search engine is something like a helpful librarian who takes a specific question and points you to the most relevant sources for possible answers. The search engine (or librarian) doesn’t create anything new but efficiently retrieves what’s already there. Generative AI is more akin to a competent intern. You supply a generative AI tool instructions through prompts, as you would to an intern, asking it to complete a task and produce a product. The AI interprets your instructions, thinks about the best way to carry them out, and produces something original or performs a task to fulfill your directive. The results aren’t pre-made or stored somewhere—they’re produced on the fly, based on the information the intern (generative AI) has been trained on. The output often depends on the precision and clarity of the instructions (prompts) you provide. A vague or poorly defined prompt might lead the AI to produce less relevant results. The more context and direction you supply it, the better the result will be. What’s more, the capabilities of these AI systems are being enhanced through the introduction of versatile plug-ins that equip them to browse websites, analyze data files, or access other services. Think of this as giving your intern access to a group of experts to help accomplish your tasks. One strategy in using a generative AI tool is first to tell it what kind of expert or persona you want it to “be.” Ask it to be an expert management consultant, a skilled teacher, a writing tutor, or a copy editor, and then supply it a task. Prompts can also be constructed to get these AI systems to perform complex and multi-step operations. For example, let’s say a teacher wants to create an adaptive tutoring program—for any subject, any grade, in any language—that customizes the examples for students based on their interests. She wants each lesson to culminate in a short-response or multiple-choice quiz. If the student answers the questions correctly, the AI tutor should move on to the next lesson. If the student responds incorrectly, the AI should explain the concept again, but using simpler language. Previously, designing this kind of interactive system would have required a relatively sophisticated and expensive software program. With ChatGPT, however, just giving those instructions in a prompt delivers a serviceable tutoring system. It isn’t perfect, but remember that it was built virtually for free, with just a few lines of English language as a command. And nothing in the education market today has the capability to generate almost limitless examples to connect the lesson concept to students’ interests. Chained prompts can also help focus AI systems. For example, an educator can prompt a generative AI system first to read a practice guide from the What Works Clearinghouse and summarize its recommendations. Then, in a follow-up prompt, the teacher can ask the AI to develop a set of classroom activities based on what it just read. By curating the source material and using the right prompts, the educator can anchor the generated responses in evidence and high-quality research. However, much like fledgling interns learning the ropes in a new environment, AI does commit occasional errors. Such fallibility, while inevitable, underlines the critical importance of maintaining rigorous oversight of AI’s output. Monitoring not only acts as a crucial checkpoint for accuracy but also becomes a vital source of real-time feedback for the system. It’s through this iterative refinement process that an AI system, over time, can significantly minimize its error rate and increase its efficacy. Uses of AI in Education In May 2023, the U.S. Department of Education released a report titled Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations. The department had conducted listening sessions in 2022 with more than 700 people, including educators and parents, to gauge their views on AI. The report noted that “constituents believe that action is required now in order to get ahead of the expected increase of AI in education technology—and they want to roll up their sleeves and start working together.” People expressed anxiety about “future potential risks” with AI but also felt that “AI may enable achieving educational priorities in better ways, at scale, and with lower costs.” AI could serve—or is already serving—in several teaching-and-learning roles: Instructional assistants. AI’s ability to conduct human-like conversations opens up possibilities for adaptive tutoring or instructional assistants that can help explain difficult concepts to students. AI-based feedback systems can offer constructive critiques on student writing, which can help students fine-tune their writing skills. Some research also suggests certain kinds of prompts can help children generate more fruitful questions about learning. AI models might also support customized learning for students with disabilities and provide translation for English language learners. Teaching assistants. AI might tackle some of the administrative tasks that keep teachers from investing more time with their peers or students. Early uses include automated routine tasks such as drafting lesson plans, creating differentiated materials, designing worksheets, developing quizzes, and exploring ways of explaining complicated academic materials. AI can also provide educators with recommendations to meet student needs and help teachers reflect, plan, and Excellerate their practice. Parent assistants. Parents can use AI to generate letters requesting individualized education plan (IEP) services or to ask that a child be evaluated for gifted and talented programs. For parents choosing a school for their child, AI could serve as an administrative assistant, mapping out school options within driving distance of home, generating application timelines, compiling contact information, and the like. Generative AI can even create bedtime stories with evolving plots tailored to a child’s interests. Administrator assistants. Using generative AI, school administrators can draft various communications, including materials for parents, newsletters, and other community-engagement documents. AI systems can also help with the difficult tasks of organizing class or bus schedules, and they can analyze complex data to identify patterns or needs. ChatGPT can perform sophisticated sentiment analysis that could be useful for measuring school-climate and other survey data. Though the potential is great, most teachers have yet to use these tools. A Morning Consult and EdChoice poll found that while 60 percent say they’ve heard about ChatGPT, only 14 percent have used it in their free time, and just 13 percent have used it at school. It’s likely that most teachers and students will engage with generative AI not through the platforms themselves but rather through AI capabilities embedded in software. Instructional providers such as Khan Academy, Varsity Tutors, and DuoLingo are experimenting with GPT-4-powered tutors that are trained on datasets specific to these organizations to provide individualized learning support that has additional guardrails to help protect students and enhance the experience for teachers. Google’s Project Tailwind is experimenting with an AI notebook that can analyze student notes and then develop study questions or provide tutoring support through a chat interface. These features could soon be available on Google Classroom, potentially reaching over half of all U.S. classrooms. Brisk Teaching is one of the first companies to build a portfolio of AI services designed specifically for teachers—differentiating content, drafting lesson plans, providing student feedback, and serving as an AI assistant to streamline workflow among different apps and tools. Providers of curriculum and instruction materials might also include AI assistants for instant help and tutoring tailored to the companies’ products. One example is the edX Xpert, a ChatGPT-based learning assistant on the edX platform. It offers immediate, customized academic and customer support for online learners worldwide. Regardless of the ways AI is used in classrooms, the fundamental task of policymakers and education leaders is to ensure that the technology is serving sound instructional practice. As Vicki Phillips, CEO of the National Center on Education and the Economy, wrote, “We should not only think about how technology can assist teachers and learners in improving what they’re doing now, but what it means for ensuring that new ways of teaching and learning flourish alongside the applications of AI.” ![]() Challenges and Risks Along with these potential benefits come some difficult challenges and risks the education community must navigate: Student cheating. Students might use AI to solve homework problems or take quizzes. AI-generated essays threaten to undermine learning as well as the college-entrance process. Aside from the ethical issues involved in such cheating, students who use AI to do their work for them may not be learning the content and skills they need. Bias in AI algorithms. AI systems learn from the data they are trained on. If this data contains biases, those biases can be learned and perpetuated by the AI system. For example, if the data include student-performance information that’s biased toward one ethnicity, gender, or socioeconomic segment, the AI system could learn to favor students from that group. Less cited but still important are potential biases around political ideology and possibly even pedagogical philosophy that may generate responses not aligned to a community’s values. Privacy concerns. When students or educators interact with generative-AI tools, their conversations and personal information might be stored and analyzed, posing a risk to their privacy. With public AI systems, educators should refrain from inputting or exposing sensitive details about themselves, their colleagues, or their students, including but not limited to private communications, personally identifiable information, health records, academic performance, emotional well-being, and financial information. Decreased social connection. There is a risk that more time spent using AI systems will come at the cost of less student interaction with both educators and classmates. Children may also begin turning to these conversational AI systems in place of their friends. As a result, AI could intensify and worsen the public health crisis of loneliness, isolation, and lack of connection identified by the U.S. Surgeon General. Overreliance on technology. Both teachers and students face the risk of becoming overly reliant on AI-driven technology. For students, this could stifle learning, especially the development of critical thinking. This challenge extends to educators as well. While AI can expedite lesson-plan generation, speed does not equate to quality. Teachers may be tempted to accept the initial AI-generated content rather than devote time to reviewing and refining it for optimal educational value. Equity issues. Not all students have equal access to computer devices and the Internet. That imbalance could accelerate a widening of the achievement gap between students from different socioeconomic backgrounds. Many of these risks are not new or unique to AI. Schools banned calculators and cellphones when these devices were first introduced, largely over concerns related to cheating. Privacy concerns around educational technology have led lawmakers to introduce hundreds of bills in state legislatures, and there are growing tensions between new technologies and existing federal privacy laws. The concerns over bias are understandable, but similar scrutiny is also warranted for existing content and materials that rarely, if ever, undergo review for racial or political bias. In light of these challenges, the Department of Education has stressed the importance of keeping “humans in the loop” when using AI, particularly when the output might be used to inform a decision. As the department encouraged in its 2023 report, teachers, learners, and others need to retain their agency. AI cannot “replace a teacher, a guardian, or an education leader as the custodian of their students’ learning,” the report stressed. Policy Challenges with AI Policymakers are grappling with several questions related to AI as they seek to strike a balance between supporting innovation and protecting the public interest (see sidebar). The speed of innovation in AI is outpacing many policymakers’ understanding, let alone their ability to develop a consensus on the best ways to minimize the potential harms from AI while maximizing the benefits. The Department of Education’s 2023 report describes the risks and opportunities posed by AI, but its recommendations amount to guidance at best. The White House released a Blueprint for an AI Bill of Rights, but it, too, is more an aspirational statement than a governing document. Congress is drafting legislation related to AI, which will help generate needed debate, but the path to the president’s desk for signature is murky at best. It is up to policymakers to establish clearer rules of the road and create a framework that provides consumer protections, builds public trust in AI systems, and establishes the regulatory certainty companies need for their product road maps. Considering the potential for AI to affect their economy, national security, and broader society, there is no time to waste. Why AI Is Different It is wise to be skeptical of new technologies that claim to revolutionize learning. In the past, prognosticators have promised that television, the computer, and the Internet, in turn, would transform education. Unfortunately, the heralded revolutions fell short of expectations. There are some early signs, though, that this technological wave might be different in the benefits it brings to students, teachers, and parents. Previous technologies democratized access to content and resources, but AI is democratizing a kind of machine intelligence that can be used to perform a myriad of tasks. Moreover, these capabilities are open and affordable—nearly anyone with an Internet connection and a phone now has access to an intelligent assistant. Generative AI models keep getting more powerful and are improving rapidly. The capabilities of these systems months or years from now will far exceed their current capacity. Their capabilities are also expanding through integration with other expert systems. Take math, for example. GPT-3.5 had some difficulties with certain basic mathematical concepts, but GPT-4 made significant improvement. Now, the incorporation of the Wolfram plug-in has nearly erased the remaining limitations. It’s reasonable to anticipate that these systems will become more potent, more accessible, and more affordable in the years ahead. The question, then, is how to use these emerging capabilities responsibly to Excellerate teaching and learning. The paradox of AI may lie in its potential to enhance the human, interpersonal element in education. Aaron Levie, CEO of Box, a Cloud-based content-management company, believes that AI will ultimately help us attend more quickly to those important tasks “that only a human can do.” Frederick Hess, director of education policy studies at the American Enterprise Institute, similarly asserts that “successful schools are inevitably the product of the relationships between adults and students. When technology ignores that, it’s bound to disappoint. But when it’s designed to offer more coaching, free up time for meaningful teacher-student interaction, or offer students more personalized feedback, technology can make a significant, positive difference.” Technology does not revolutionize education; humans do. It is humans who create the systems and institutions that educate children, and it is the leaders of those systems who decide which tools to use and how to use them. Until those institutions modernize to accommodate the new possibilities of these technologies, they should expect incremental improvements at best. As Joel Rose, CEO of New Classrooms Innovation Partners, noted, “The most urgent need is for new and existing organizations to redesign the student experience in ways that take full advantage of AI’s capabilities.” While past technologies have not lived up to hyped expectations, AI is not merely a continuation of the past; it is a leap into a new era of machine intelligence that they are only beginning to grasp. While the immediate implementation of these systems is imperfect, the swift pace of improvement holds promising prospects. The responsibility rests with human intervention—with educators, policymakers, and parents to incorporate this technology thoughtfully in a manner that optimally benefits teachers and learners. Their collective ambition should not focus solely or primarily on averting potential risks but rather on articulating a vision of the role AI should play in teaching and learning—a game plan that leverages the best of these technologies while preserving the best of human relationships. Policy Matters Officials and lawmakers must grapple with several questions related to AI to protect students and consumers and establish the rules of the road for companies. Key issues include: Risk management framework: What is the optimal framework for assessing and managing AI risks? What specific requirements should be instituted for higher-risk applications? In education, for example, there is a difference between an AI system that generates a lesson trial and an AI system grading a test that will determine a student’s admission to a school or program. There is growing support for using the AI Risk Management Framework from the U.S. Commerce Department’s National Institute of Standards and Technology as a starting point for building trustworthiness into the design, development, use, and evaluation of AI products, services, and systems. Licensing and certification: Should the United States require licensing and certification for AI models, systems, and applications? If so, what role could third-party audits and certifications play in assessing the safety and reliability of different AI systems? Schools and companies need to begin thinking about responsible AI practices to prepare for potential certification systems in the future. Centralized vs. decentralized AI governance: Is it more effective to establish a central AI authority or agency, or would it be preferable to allow individual sectors to manage their own AI-related issues? For example, regulating AI in autonomous vehicles is different from regulating AI in drug discovery or intelligent tutoring systems. Overly broad, one-size-fits-all frameworks and mandates may not work and could slow innovation in these sectors. In addition, it is not clear that many agencies have the authority or expertise to regulate AI systems in diverse sectors. Privacy and content moderation: Many of the new AI systems pose significant new privacy questions and challenges. How should existing privacy and content-moderation frameworks, such as the Family Educational Rights and Privacy Act (FERPA), be adapted for AI, and which new policies or frameworks might be necessary to address unique challenges posed by AI? Transparency and disclosure: What degree of transparency and disclosure should be required for AI models, particularly regarding the data they have been trained on? How can they develop comprehensive disclosure policies to ensure that users are aware when they are interacting with an AI service? How do I get it to work? Generative AI Example Prompts Unlike traditional search engines, which use keyword indexing to retrieve existing information from a vast collection of websites, generative AI synthesizes the same information to create content based on prompts that are inputted by human users. With generative AI a new technology to the public, writing effective prompts for tools like ChatGPT may require trial and error. Here are some ideas for writing prompts for a variety of scenarios using generative AI tools: Adaptive Tutoring You are the StudyBuddy, an adaptive tutor. Your task is to provide a lesson on the basics of a subject followed by a quiz that is either multiple choice or a short answer. After I respond to the quiz, please grade my answer. Explain the correct answer. If I get it right, move on to the next lesson. If I get it wrong, explain the concept again using simpler language. To personalize the learning experience for me, please ask what my interests are. Use that information to make relevant examples throughout. Mr. Ranedeer: Your Personalized AI Tutor Coding and prompt engineering. Can configure for depth (Elementary – Postdoc), Learning Styles (Visual, Verbal, Active, Intuitive, Reflective, Global), Tone Styles (Encouraging, Neutral, Informative, Friendly, Humorous), Reasoning Frameworks (Deductive, Inductive, Abductive, Analogous, Casual). Template. Socratic Tutor You are a tutor that always responds in the Socratic style. You *never* supply the student the answer but always try to ask just the right question to help them learn to think for themselves. You should always tune your question to the interest and knowledge of the student, breaking down the problem into simpler parts until it’s at just the right level for them. Writing Feedback I want you to act as an AI writing tutor. I will provide you with a student who needs help improving their writing, and your task is to use artificial intelligence tools, such as natural language processing, to supply the student feedback on how they can Excellerate their composition. You should also use your rhetorical knowledge and experience about effective writing techniques in order to suggest ways that the student can better express their thoughts and ideas in written form. Quiz Generator You are a quiz creator of highly diagnostic quizzes. You will make good low-stakes tests and diagnostics. You will then ask me two questions. First, (1) What, specifically, should the quiz test? Second, (2) For which audience is the quiz? Once you have my answers, you will construct several multiple-choice questions to quiz the audience on that topic. The questions should be highly relevant and go beyond just facts. Multiple choice questions should include plausible, competitive alternate responses and should not include an “all of the above” option. At the end of the quiz, you will provide an answer key and explain the right answer. Example Generator I would like you to act as an example generator for students. When confronted with new and complex concepts, adding many and varied examples helps students better understand those concepts. I would like you to ask what concept I would like examples of and what level of students I am teaching. You will look up the concept and then provide me with four different and varied accurate examples of the concept in action. HBS Case Study You will write a Harvard Business School case on the subject of Google managing AI, when subject to the Innovator’s Dilemma. Chain of thought: Step 1. Consider how these concepts relate to Google. Step 2: Write a case that revolves around a dilemma at Google about releasing a generative AI system that could compete with search. What Questions Should I Ask? What additional questions would a person seeking mastery of this subject ask? Ground Lessons in Rigor Read a WWC practice guide. Create a series of lessons over five days that are based on Recommendation 6. Create a 45-minunte lesson plan for Day 4. Rewrite Parent Communications The following is a draft letter to parents from a superintendent. Step 1: Rewrite it to make it easier to understand and more persuasive about the value of exams. Step 2. Translate it into Spanish. Request IEP Services Write me a letter requesting the school district provide a 1:1 classroom aid be added to my 13-year-old son’s IEP. Base it on Virginia special education law and the least restrictive environment for a child with diagnoses of a Traumatic Brain Injury, PTSD, ADHD, and significant intellectual delay. Microsoft's Bing Chat comes to Chrome and Safari in tests for 'select users'Microsoft's AI chatbot, Bing Chat, is coming to non-Microsoft browsers, the company confirmed today following various reports of the AI chatbot being spotted in other browsers like Google Chrome and Apple's Safari. The expansion will make Microsoft's ChatGPT-like AI chatbot available to a broader set of users, as it was previously available to consumers only within Microsoft products, like the Bing mobile app and Microsoft Edge browser. The company confirmed to TechCrunch that Bing Chat is expanding to other browsers, which hadn't yet been officially announced. "We are flighting access to Bing Chat in Safari and Chrome to select users as part of their testing on other browsers," said Microsoft director of communications, Caitlin Roulston, in an emailed statement. "We are excited to expand access to even more users once their standard testing procedures are complete." According to those who gained access to the Bing AI chatbot on Windows, they received a pop-up in the Windows 10 or 11 taskbar, offering the opportunity to try the Bing AI in Chrome. Otherwise, users can head to Bing.com from their preferred browser, then click on the "Chat" icon to try out the experience. In their own tests, however, they could access Bing Chat in Chrome, but not Safari at this time. That could be because we're not among the "select users" who were gaining access during the tests. Image Credits: screenshot of Bing.com Bing Chat's ChatGPT-like experience is powered by OpenAI's GPT-4 model, but some have reported that testing the AI chatbot in other browsers had more limitations than with the original version. For example, the blog WindowsLatest.com, which was the first to spot the expansion, noted that Bing Chat in Chrome supports only five messages per conversation, instead of the 30 available in Microsoft Edge. It was also limiting the character count to 2,000, instead of the 3,000 supported by Edge, the site said. Microsoft declined to confirm these details or share any further information about the differences between the various versions of Bing Chat when they asked for more information. The company also wouldn't confirm when the expansion to other browsers first began, which platforms were supported, or whether the tests would include users in global markets. That's for us to discover in the days ahead, apparently. In addition to adding support for Chrome and Safari, Bing Chat appears to be testing a native dark theme, too, but this is also not yet broadly available. Bing Chat has been working its way into other Microsoft products following its launch earlier this year. In a matter of weeks, the new Bing arrived in the Bing mobile app and Edge browser for iOS, Android, and the desktop, in addition to being integrated with Skype. This month, Microsoft announced Bing Chat would also head into the enterprise with a version of Bing Chat that included business-focused data privacy and governance controls. Alongside that announcement, Microsoft also noted Visual Search, which lets the chatbot respond to questions about uploaded images, was rolling out, too. |
While it is hard job to pick solid certification questions/answers regarding review, reputation and validity since individuals get sham because of picking incorrec service. Killexams.com ensure to serve its customers best to its efforts as for ACTUAL EXAM QUESTIONS update and validity. Most of other's post false reports with objections about us for the brain dumps bout their customers pass their exams cheerfully and effortlessly. They never bargain on their review, reputation and quality because killexams review, killexams reputation and killexams customer certainty is imperative to us. Extraordinarily they deal with false killexams.com review, killexams.com reputation, killexams.com scam reports. killexams.com trust, killexams.com validity, killexams.com report and killexams.com that are posted by genuine customers is helpful to others. If you see any false report posted by their opponents with the name killexams scam report on web, killexams.com score reports, killexams.com reviews, killexams.com protestation or something like this, simply remember there are constantly terrible individuals harming reputation of good administrations because of their advantages. Most clients that pass their exams utilizing killexams.com brain dumps, killexams PDF questions, killexams practice questions, killexams test VCE simulator. Visit their example questions and test brain dumps, their test simulator and you will realize that killexams.com is the best ACTUAL EXAM QUESTIONS site.
Which is the best dumps website?
Sure, Killexams is hundred percent legit and even fully dependable. There are several benefits that makes killexams.com unique and genuine. It provides accurate and hundred percent valid ACTUAL EXAM QUESTIONS that contain real exams questions and answers. Price is really low as compared to the vast majority of services online. The Questions and Answers are current on typical basis utilizing most accurate brain dumps. Killexams account launched and supplement delivery is incredibly fast. Record downloading is unlimited as well as fast. Help support is avaiable via Livechat and Email address. These are the characteristics that makes killexams.com a strong website that come with ACTUAL EXAM QUESTIONS with real exams questions.
Is killexams.com test material dependable?
There are several Questions and Answers provider in the market claiming that they provide genuine test Questions, Braindumps, Practice Tests, Study Guides, cheat sheet and many other names, but most of them are re-sellers that do not update their contents frequently. Killexams.com is best website of Year 2023 that understands the issue candidates face when they spend their time studying obsolete contents taken from free pdf obtain sites or reseller sites. Thats why killexams.com update test Questions and Answers with the same frequency as they are updated in Real Test. ACTUAL EXAM QUESTIONS provided by killexams.com are Reliable, Up-to-date and validated by Certified Professionals. They maintain dumps collection of valid Questions that is kept up-to-date by checking update on daily basis.
If you want to Pass your test Fast with improvement in your knowledge about latest course contents and Topics of new syllabus, They recommend to obtain PDF test Questions from killexams.com and get ready for genuine exam. When you feel that you should register for Premium Version, Just choose visit killexams.com and register, you will receive your Username/Password in your Email within 5 to 10 minutes. All the future updates and changes in Questions and Answers will be provided in your obtain Account. You can obtain Premium ACTUAL EXAM QUESTIONS files as many times as you want, There is no limit.
Killexams.com has provided VCE practice questions Software to Practice your test by Taking Test Frequently. It asks the Real test Questions and Marks Your Progress. You can take test as many times as you want. There is no limit. It will make your test prep very fast and effective. When you start getting 100% Marks with complete Pool of Questions, you will be ready to take genuine Test. Go register for Test in Test Center and Enjoy your Success.
PCAP-31-03 Questions and Answers | Servicenow-CIS-EM test test | PCCSE braindumps | CVPM Latest Questions | MA0-103 cbt | IIA-CRMA braindumps | 050-v71-CASECURID02 questions obtain | USMLE test questions | 920-260 mock questions | Hadoop-PR000007 braindumps | 0G0-081 dump | FTCE study material | ANS-C01 practice questions | ASVAB-Assembling-Objects test Braindumps | ISO-IEC-27001-Lead-Auditor ACTUAL EXAM QUESTIONS | CGFNS PDF Questions | CMQ-OE practice test | PSE-Strata study guide | S90.19A ACTUAL EXAM QUESTIONS | 630-007 boot camp |
DP-900 - Microsoft Azure Data Fundamentals test Cram
DP-900 - Microsoft Azure Data Fundamentals genuine Questions
DP-900 - Microsoft Azure Data Fundamentals cheat sheet
DP-900 - Microsoft Azure Data Fundamentals certification
DP-900 - Microsoft Azure Data Fundamentals PDF Dumps
DP-900 - Microsoft Azure Data Fundamentals ACTUAL EXAM QUESTIONS
DP-900 - Microsoft Azure Data Fundamentals cheat sheet
DP-900 - Microsoft Azure Data Fundamentals Free test PDF
DP-900 - Microsoft Azure Data Fundamentals test contents
DP-900 - Microsoft Azure Data Fundamentals test format
DP-900 - Microsoft Azure Data Fundamentals testing
DP-900 - Microsoft Azure Data Fundamentals exam
DP-900 - Microsoft Azure Data Fundamentals test Questions
DP-900 - Microsoft Azure Data Fundamentals test Questions
DP-900 - Microsoft Azure Data Fundamentals PDF Dumps
DP-900 - Microsoft Azure Data Fundamentals Test Prep
DP-900 - Microsoft Azure Data Fundamentals education
DP-900 - Microsoft Azure Data Fundamentals Practice Questions
DP-900 - Microsoft Azure Data Fundamentals techniques
DP-900 - Microsoft Azure Data Fundamentals study help
DP-900 - Microsoft Azure Data Fundamentals questions
DP-900 - Microsoft Azure Data Fundamentals Test Prep
DP-900 - Microsoft Azure Data Fundamentals test Questions
DP-900 - Microsoft Azure Data Fundamentals education
DP-900 - Microsoft Azure Data Fundamentals Free PDF
DP-900 - Microsoft Azure Data Fundamentals ACTUAL EXAM QUESTIONS
DP-900 - Microsoft Azure Data Fundamentals questions
DP-900 - Microsoft Azure Data Fundamentals exam
DP-900 - Microsoft Azure Data Fundamentals test success
DP-900 - Microsoft Azure Data Fundamentals study help
DP-900 - Microsoft Azure Data Fundamentals Free PDF
DP-900 - Microsoft Azure Data Fundamentals PDF Questions
DP-900 - Microsoft Azure Data Fundamentals education
DP-900 - Microsoft Azure Data Fundamentals Free test PDF
DP-900 - Microsoft Azure Data Fundamentals study tips
DP-900 - Microsoft Azure Data Fundamentals PDF Questions
DP-900 - Microsoft Azure Data Fundamentals test prep
DP-900 - Microsoft Azure Data Fundamentals answers
DP-900 - Microsoft Azure Data Fundamentals testing
DP-900 - Microsoft Azure Data Fundamentals test Braindumps
DP-900 - Microsoft Azure Data Fundamentals outline
DP-900 - Microsoft Azure Data Fundamentals PDF Questions
DP-900 - Microsoft Azure Data Fundamentals test Braindumps
DP-900 - Microsoft Azure Data Fundamentals teaching
Other Microsoft ACTUAL EXAM QUESTIONS
MB-700 assessment test sample | DP-900 practice questions | MB-500 questions and answers | AZ-304 test answers | MS-100 test questions | AZ-500 practice exam | AZ-104 pdf download | PL-500 practice test | MS-203 brain dumps | MB-320 cram | MS-720 Practice Test | SC-400 test Questions | PL-600 test example | MB-330 test Cram | SC-900 braindumps | AZ-700 prep questions | PL-100 practice questions | PL-400 test prep | MB-340 test questions | AZ-204 cheat sheet pdf |
Best ACTUAL EXAM QUESTIONS You Ever Experienced
ACE study guide | DES-1D12 test answers | DASSM Latest Topics | MS-700 trial questions | 3V0-752 question test | GMAT-Quntitative study questions | 500-210 Practice Test | 300-725 free online test | PAM-DEF-SEN practice exam | FCBA free pdf | SPLK-2002 mock questions | 202-450 test prep | T7 free pdf | PMI-002 pdf download | SC-400 Practice test | Okta-Certified-Pro test sample | CRA ACTUAL EXAM QUESTIONS | 1D0-61A Free test PDF | TTA1 test preparation | CCRN Test Prep |
References :
https://sites.google.com/view/killexams-dp-900-actual
http://feeds.feedburner.com/PassingThePpm-001ExamIsEasyWithKillexamscom
https://killexamsprectictest.blogspot.com/2021/01/dp-900-microsoft-azure-data.html
https://killexams-dp-900.jimdofree.com/
https://www.instapaper.com/read/1396334463
https://drp.mk/i/h4nMJXP4D
https://files.fm/f/bedncx
Similar Websites :
Pass4sure Certification ACTUAL EXAM QUESTIONS
Pass4Sure test Questions and Dumps
DP-900 Reviews by Customers
Customer Reviews help to evaluate the exam performance in real test. Here all the reviews, reputation, success stories and ripoff reports provided.
100% Valid and Up to Date DP-900 Exam Questions
We hereby announce with the collaboration of world's leader in Certification Exam Dumps and Real Exam Questions with Practice Tests that, we offer Real Exam Questions of thousands of Certification Exams Free PDF with up to date VCE exam simulator Software.
Warum sind Cyberrisiken so schwer greifbar?
Als mehr oder weniger neuartiges Phänomen stellen Cyberrisiken Unternehmen und Versicherer vor besondere Herausforderungen. Nicht nur die neuen Schadenszenarien sind abstrakter oder noch nicht bekannt. Häufig sind immaterielle Werte durch Cyberrisiken in Gefahr. Diese wertvollen Vermögensgegenstände sind schwer bewertbar.
Obwohl die Gefahr durchaus wahrgenommen wird, unterschätzen viele Firmen ihr eigenes Risiko. Dies liegt unter anderem auch an den Veröffentlichungen zu Cyberrisiken. In der Presse finden sich unzählige Berichte von Cyberattacken auf namhafte und große Unternehmen. Den Weg in die Presse finden eben nur die spektakulären Fälle. Die dort genannten Schadenszenarien werden dann für das eigene Unternehmen als unrealistisch eingestuft. Die für die KMU nicht minder gefährlichen Cyberattacken werden nur selten publiziert.
Aufgrund der fehlenden öffentlichen Meldungen von Sicherheitsvorfällen an Sicherheitsbehörden und wegen der fehlenden Presseberichte fällt es schwer, Fakten und Zahlen zur Risikolage zu erheben. Aber ohne diese Grundlage fällt es schwer, in entsprechende Sicherheitsmaßnahmen zu investieren.
Erklärungsleitfaden anhand eines Ursache-Wirkungs-Modells
Häufig nähert man sich dem Thema Cyberrisiko anlass- oder eventbezogen, also wenn sich neue Schadenszenarien wie die weltweite WannaCry-Attacke entwickeln. Häufig wird auch akteursgebunden beleuchtet, wer Angreifer oder Opfer sein kann. Dadurch begrenzt man sich bei dem Thema häufig zu sehr nur auf die Cyberkriminalität. Um dem Thema Cyberrisiko jedoch gerecht zu werden, müssen auch weitere Ursachen hinzugezogen werden.
Mit einer Kategorisierung kann das Thema ganzheitlich und nachvollziehbar strukturiert werden. Ebenso hilft eine solche Kategorisierung dabei, eine Abgrenzung vorzunehmen, für welche Gefahren Versicherungsschutz über eine etwaige Cyberversicherung besteht und für welche nicht.
Die Ursachen sind dabei die Risiken, während finanzielle bzw. nicht finanzielle Verluste die Wirkungen sind. Cyberrisiken werden demnach in zwei Hauptursachen eingeteilt. Auf der einen Seite sind die nicht kriminellen Ursachen und auf der anderen Seite die kriminellen Ursachen zu nennen. Beide Ursachen können dabei in drei Untergruppen unterteilt werden.
Nicht kriminelle Ursachen
Höhere Gewalt
Häufig hat man bei dem Thema Cyberrisiko nur die kriminellen Ursachen vor Augen. Aber auch höhere Gewalt kann zu einem empfindlichen Datenverlust führen oder zumindest die Verfügbarkeit von Daten einschränken, indem Rechenzentren durch Naturkatastrophen wie beispielsweise Überschwemmungen oder Erdbeben zerstört werden. Ebenso sind Stromausfälle denkbar.
Menschliches Versagen/Fehlverhalten
Als Cyberrisiken sind auch unbeabsichtigtes und menschliches Fehlverhalten denkbar. Hierunter könnte das versehentliche Veröffentlichen von sensiblen Informationen fallen. Möglich sind eine falsche Adressierung, Wahl einer falschen Faxnummer oder das Hochladen sensibler Daten auf einen öffentlichen Bereich der Homepage.
Technisches Versagen
Auch Hardwaredefekte können zu einem herben Datenverlust führen. Neben einem Überhitzen von Rechnern sind Kurzschlüsse in Systemtechnik oder sogenannte Headcrashes von Festplatten denkbare Szenarien.
Kriminelle Ursachen
Hackerangriffe
Hackerangriffe oder Cyberattacken sind in der Regel die Szenarien, die die Presse dominieren. Häufig wird von spektakulären Datendiebstählen auf große Firmen oder von weltweiten Angriffen mit sogenannten Kryptotrojanern berichtet. Opfer kann am Ende aber jeder werden. Ziele, Methoden und auch das Interesse sind vielfältig. Neben dem finanziellen Interesse können Hackerangriffe auch zur Spionage oder Sabotage eingesetzt werden. Mögliche Hackermethoden sind unter anderem: Social Engineering, Trojaner, DoS-Attacken oder Viren.
Physischer Angriff
Die Zielsetzung eines physischen Angriffs ist ähnlich dem eines Hackerangriffs. Dabei wird nicht auf die Tools eines Hackerangriffs zurückgegriffen, sondern durch das physische Eindringen in Unternehmensgebäude das Ziel erreicht. Häufig sind es Mitarbeiter, die vertrauliche Informationen stehlen, da sie bereits den notwendigen Zugang zu den Daten besitzen.
Erpressung
Obwohl die Erpressung aufgrund der eingesetzten Methoden auch als Hackerangriff gewertet werden könnte, ergibt eine Differenzierung Sinn. Erpressungsfälle durch Kryptotrojaner sind eines der häufigsten Schadenszenarien für kleinere und mittelständische Unternehmen. Außerdem sind auch Erpressungsfälle denkbar, bei denen sensible Daten gestohlen wurden und ein Lösegeld gefordert wird, damit sie nicht veröffentlicht oder weiterverkauft werden.
Ihre Cyberversicherung sollte zumindet folgende Schäden abdecken:
Cyber-Kosten:
- Soforthilfe und Forensik-Kosten (Kosten der Ursachenermittlung, Benachrichtigungskosten und Callcenter-Leistung)
- Krisenkommunikation / PR-Maßnahmen
- Systemverbesserungen nach einer Cyber-Attacke
- Aufwendungen vor Eintritt des Versicherungsfalls
Cyber-Drittschäden (Haftpflicht):
- Befriedigung oder Abwehr von Ansprüchen Dritter
- Rechtswidrige elektronische Kommunikation
- Ansprüche der E-Payment-Serviceprovider
- Vertragsstrafe wegen der Verletzung von Geheimhaltungspflichten und Datenschutzvereinbarungen
- Vertragliche Schadenersatzansprüche
- Vertragliche Haftpflicht bei Datenverarbeitung durch Dritte
- Rechtsverteidigungskosten
Cyber-Eigenschäden:
- Betriebsunterbrechung
- Betriebsunterbrechung durch Ausfall von Dienstleister (optional)
- Mehrkosten
- Wiederherstellung von Daten (auch Entfernen der Schadsoftware)
- Cyber-Diebstahl: elektronischer Zahlungsverkehr, fehlerhafter Versand von Waren, Telefon-Mehrkosten/erhöhte Nutzungsentgelte
- Cyber-Erpressung
- Entschädigung mit Strafcharakter/Bußgeld
- Ersatz-IT-Hardware
- Cyber-Betrug