>> Prompting: How to Ask AI

How to Ask AI: The Power of Prompting Artificial Intelligence to Innovate and Increase Productivity

By Walter Rodriguez, PhD, PE

Summary

Drawing inspiration from the Socratic method, a timeless approach to inquiry, can inform our interactions with Artificial Intelligence (AI). The rise of AI has transformed the way we interact with machines. One crucial aspect of this interaction is prompting, the art of asking AI the right questions to elicit responses, innovate, and increase productivity. Effective prompting is essential for harnessing the full potential of AI, yet it remains a poorly understood skill. This article provides a guide on how to ask AI, exploring the fundamentals of prompting, types of prompts, and best practices for crafting effective prompts. And to elicit more meaningful queries and responses to AI assistants, models, and systems, such as Anthoropic’s Claude 3 Opus, Google’s Gemini Advanced, Meta’s LLaMA, and OpenAI’s ChatGPT, among other large language models. Prompting can also provide insights when interacting with humans since AI assistants are based on human data, machine learning algorithms, and natural language processing (NLP) techniques.

Introduction

The ability to ask the right questions has become more crucial. Questions are the building blocks of knowledge, innovation, and progress. They spark curiosity, drive exploration, and unlock solutions to complex problems. However, not all questions are created equal. The art of asking effective questions lies in the skillful craft of prompting or prompt engineering in the Artificial Intelligence domain.

Artificial intelligence (AI) and natural language processing (NLP) are transforming the dynamics of questioning and answering. AI-driven systems can sift through immense datasets, discern intricate patterns, and produce instantaneous responses, thus enhancing human capacities to unparalleled levels. Below are a few commercially available systems.

Claude \ Anthropic—Claude is a family of foundational AI models used in a variety of applications. Users can talk directly with Claude at claude.ai to brainstorm ideas, analyze images, and process long documents. Developers and businesses, you can now get API access and build directly on top of our AI infrastructure.

‎Gemini Advanced—a capable model for reasoning, following instructions, coding, and creative inspiration.

LLaMA—a free and open-source large language model developed by Meta AI. It is trained on a dataset of 1.4 trillion tokens and can generate human-like text.

Stable Diffusion—a text-to-image AI model that generates images based on prompts. It is available for free and can be run on a personal computer.

ChatGPT Codex—a generative AI model that can generate source code for new computer programs. It is trained on a dataset of programming languages and can be used for free.

ElevenLabs' context-aware synthesis tools—a generative AI model that can generate natural-sounding speech synthesis and text-to-speech capabilities. It is available for free and can be used for personal projects.

MusicLM—a generative AI model that can generate new musical samples based on text descriptions. It is available for free and can be used for personal projects.

GPTZero—a free AI text detector that can recognize text generated by generative AI models. It is available for free and can be used for personal projects.

AI assistants are trained on large datasets of human language, behavior, and preferences. This data can come from various sources, such as User interactions with digital devices (e.g., search queries, chat logs); Social media platforms; Online reviews and ratings; Surveys and feedback forms; and Human-generated content (e.g., books, articles, websites).

AI assistants use machine learning algorithms to learn from human data and improve their performance over time. These algorithms can be Supervised learning (e.g., classification, regression); Unsupervised learning (e.g., clustering, dimensionality reduction); Reinforcement learning (e.g., trial and error, reward-based learning); and Natural Language Processing (NLP).

AI assistants employ NLP techniques to understand and generate human-like language. These techniques include Tokenization (breaking down text into individual words or tokens); Part-of-speech tagging (identifying word types, such as nouns, verbs, and adjectives); Named entity recognition (identifying specific entities, such as names, locations, and organizations); Sentiment analysis (determining the emotional tone or sentiment of text); Dialogue management (generating responses to user input). By combining these elements, AI assistants can learn to recognize patterns, understand context, and generate human-like responses. However, it's important to note that AI assistants can make mistakes. Ongoing training and refinement are necessary to improve their performance and accuracy. Nevertheless, Artificial Intelligence (AI) is a powerful tool to drive innovation and increase productivity in various industries. You can leverage AI for innovation and productivity, as follows:

Automation: AI can automate repetitive and mundane tasks, freeing up human resources for more creative and strategic work.

Data Analysis: AI can quickly process and analyze large amounts of data, providing valuable insights and patterns that humans might miss.

Predictive Maintenance: AI-powered predictive maintenance can help prevent equipment failures, reducing downtime and increasing overall productivity.

Virtual Assistants: AI-powered virtual assistants can help with tasks such as scheduling, email management, and research, freeing up time for more important tasks.

Chatbots: AI-powered chatbots can provide 24/7 customer support, helping to resolve issues and improve customer satisfaction.

Content Generation: AI can generate content, such as articles, social media posts, and marketing materials, freeing up human resources for more strategic work.

Research and Development: AI can help with research and development by analyzing data, identifying patterns, and providing insights that can lead to new innovations.

Process Optimization: AI can analyze business processes and provide recommendations for optimization, leading to increased efficiency and productivity.

Employee Augmentation: AI can augment human capabilities, providing employees with real-time data and insights to make better decisions.

Innovation Hubs: AI can be used to create innovation hubs, where companies can experiment with new ideas and technologies, leading to new innovations and products.

Supply Chain Optimization: AI can optimize supply chain management, predicting demand, managing inventory, and streamlining logistics.

Customer Service: AI-powered customer service can provide personalized support, improving customer satisfaction and loyalty.

Marketing: AI can help with marketing efforts, providing personalized recommendations, predicting customer behavior, and optimizing marketing campaigns.

Sales: AI can help with sales efforts, providing personalized recommendations, predicting customer behavior, and optimizing sales processes.

HR: AI can help with HR tasks, such as recruitment, talent management, and employee engagement.

Of course, AI is a tool, not a replacement for human ingenuity and creativity. By leveraging AI in these ways, you can drive innovation and increase productivity but always consider the human perspective and ensure that AI is used responsibly and ethically.

Prompt Engineering: Socratic Inspiration

The Socratic method, employed by the ancient Greek philosopher Socrates, offers valuable insights for prompting AI (Socrates, 380 BCE). Socrates' approach emphasized asking probing questions to expose assumptions and clarify understanding. Similarly, when interacting with AI, we should ask targeted questions or requests to expose AI's assumptions and clarify its understanding.

Sample Prompt: Write an email to thank our employees or colleagues for (insert what you are thankful for).

A well-crafted prompt should be clear, concise, and unambiguous (Hovy et al., 2021). It should also be specific, avoiding vague or open-ended questions (Gao et al., 2021). Effective prompts leverage AI's strengths while minimizing weaknesses, such as bias and hallucination (Bolukbasi et al., 2016).

Sample Prompt: Convert the attached file from [current file format] to [desired file format]

Of course, attach the file.

Sample Prompt for Creating a Resume

Create a professional resume for a software engineer with 5 years of experience. The resume should highlight the candidate's technical skills, relevant work experience, and educational background. Ensure that the resume is well-organized, concise, and visually appealing. Use appropriate formatting, bullet points, and sections to make it easy to read and understand.

Required Sections:

Header: Include the candidate's name, contact information (phone number, email address), and optionally, a link to their LinkedIn profile or personal website.

Summary/Objective: Write a brief summary highlighting the candidate's expertise, career goals, and key accomplishments.

Technical Skills: List the candidate's technical skills, emphasizing proficiency in programming languages, frameworks, tools, and technologies relevant to software engineering.

Work Experience: Provide details of the candidate's work experience, including job titles, company names, dates of employment, and descriptions of responsibilities and achievements in each role.

Education: List the candidate's educational background, including degrees earned, institution names, dates of attendance, and any relevant coursework or academic achievements.

Additional Tips:

Use action verbs to describe accomplishments and responsibilities in the work experience section.

Quantify achievements where possible (e.g., "Implemented a new feature that reduced processing time by 30%").

Tailor the resume to the specific job description or industry, highlighting relevant skills and experiences.

Keep the resume length to one page, unless the candidate has extensive experience or qualifications that warrant additional pages.

Sample Format

[Name]

[Contact Information]

[Summary/Objective]

[Technical Skills]

[Work Experience]

- [Job Title], [Company Name], [Dates]

- Description of responsibilities and achievements

- [Job Title], [Company Name], [Dates]

- Description of responsibilities and achievements

[Education]

- [Degree], [Institution Name], [Dates]

- Relevant coursework or academic achievements (if applicable)

AI has revolutionized numerous domains, from natural language processing to image recognition (Kurzweil, 2005). However, AI's ability to process human language is limited by the quality of the prompts it receives (Gao et al., 2021). Prompting is the process of crafting input that elicits a desired response from AI, and it requires a deep understanding of language, context, and AI's capabilities.

Prompt engineering is the deliberate design and formulation of prompts, queries, or inquiries to elicit specific responses, insights, or actions. It involves understanding the context, audience, and desired outcomes to tailor questions that lead to meaningful discoveries and outcomes. In business, education, healthcare, or everyday life, prompt engineering is essential

Prompt engineering is about empowering individuals to ask better questions. It's about moving beyond surface-level inquiries to delve deeper into the heart of a matter. It's about framing questions to encourage critical thinking, creativity, and collaboration. In a world driven by data and information, asking insightful questions is a valuable skill that can set individuals apart and drive success in various domains.

Technology, particularly artificial intelligence (AI) and natural language processing (NLP) are revolutionizing how we ask and answer questions. AI-powered systems can analyze vast amounts of data, identify patterns, and generate responses in real-time, augmenting human capabilities in unprecedented ways. AI virtual assistants and recommendation algorithms have become intertwined with our daily interactions, shaping how we seek and receive information.

However, with great power comes great responsibility. As we harness the potential of technology to enhance prompting, we must also navigate ethical considerations and challenges. Privacy, bias, and manipulation loom large in AI-driven prompt engineering. It's essential to ensure transparency, fairness, and accountability in designing and deploying prompts and AI systems to mitigate potential risks and safeguard against unintended consequences.

Sample Prompt

Research and write a paper draft in APA format on the topic of [Enter detailed title of paper]. The paper should consist of an introduction, literature review, methodology, findings or discussion, and conclusion sections. Ensure that all sources are properly cited using APA style guidelines. The paper should be well-organized, clear, and provide evidence-based insights into the relationship between social media usage and mental health outcomes in the adolescent population.

Required Sections:

Introduction: Provide an overview of the topic and its significance, as well as the purpose and scope of the paper. Clearly state the research question or hypothesis.

Literature Review: Summarize existing research and scholarly articles on the impact of social media on mental health among adolescents. Analyze key findings, theories, and methodologies used in previous studies.

Methodology: If applicable (e.g., if conducting original research), describe the research design, sample characteristics, data collection methods, and data analysis techniques.

Findings/Discussion: Present the main findings or discuss the implications of the literature reviewed. Consider factors such as the role of social media platforms, the prevalence of mental health issues, potential mechanisms of influence, and any mitigating factors.

Conclusion: Summarize the key points of the paper, discuss any limitations or areas for future research, and offer concluding remarks on the overall impact of social media on adolescent mental health.

Additional Instructions:

Use third-person voice and maintain a formal tone throughout the paper.

Provide in-text citations for all sources used, following APA style guidelines.

Include a reference list at the end of the paper, listing all sources cited in alphabetical order.

Aim for clarity, coherence, and logical flow between sections.

Ensure proper formatting according to APA guidelines, including title page, running head, page numbers, headings, and margins.

Sample Format:

Title

Abstract

Introduction

Literature Review

Methodology

Findings or Discussion

Conclusion

References

Further, prompt engineering plays a pivotal role in driving progress and competitiveness. Companies that excel in prompt engineering can leverage insights—from customer feedback, market research, and data analysis to inform strategic decisions, develop innovative products, and deliver exceptional customer experiences. From crafting compelling survey questions to designing intuitive user interfaces, prompt engineering permeates every aspect of product development and marketing strategy.

Prompt engineering holds the key to fostering critical thinking and lifelong curiosity. Educators can design prompts that challenge students to think critically, analyze information, and construct coherent arguments. By crafting thought-provoking questions and fostering a culture of inquiry, educators can cultivate a deeper understanding of subjects and instill a lifelong love of learning in their students.

Types of Prompts

Prompts can be categorized into three types:

Specific prompts: Elicit a precise response, such as a definition or a fact.

Open-ended prompts: Encourage AI to generate creative content, like stories or ideas.

Hybrid prompts: Combine specific and open-ended elements to allow AI to generate creative responses within boundaries.

Best Practices for Crafting Effective Prompts

Define the task: Clearly articulate the desired response or outcome.

Use natural language: Employ everyday language, avoiding technical jargon.

Provide context: Offer relevant information to help AI understand the prompt.

Test and refine: Iterate on prompts to optimize results.

Ask follow-up questions: Engage in a dialogue with AI, seeking clarification and probing assumptions, just as Socrates would.

Prompting: How to Ask AI for Effective Responses

Prompting, or providing input instructions to an artificial intelligence (AI) system, is crucial in obtaining high-quality outputs. Effective prompting can enhance the AI's comprehension, leading to more relevant and coherent responses (Ye et al., 2023). This article explores strategies for prompting AI assistants to maximize their potential.

Provide Context: AI systems, while highly capable, lack the inherent context that humans possess. Providing relevant background information or framing the task appropriately can significantly improve the AI's understanding (Bommasani et al., 2021). For example, instead of asking "What is the capital of France?" it is better to prompt with "In the context of countries and major cities, what is the capital of France?"

Sample Prompt: Story

I am writing a fictional story and need to incorporate unforeseen plot twists to elevate tension and captivate readers' attention, leaving them eagerly anticipating each subsequent development. Craft these twists seamlessly within [include your narrative], ensuring they contribute to the overarching intrigue and suspense of my story. [Provide details about your story, including its setting, characters, plot lines, and relationships, to contextualize your inquiry. This information will enable tailored advice on integrating plot twists effectively into your specific storyline*.]

*Consider elements such as character motivations, hidden agendas, unexpected revelations, and shifts in alliances or loyalties to introduce twists that challenge readers' assumptions and keep them engaged with your narrative. Aim to strike a balance between unpredictability and coherence, ensuring that each twist feels both surprising and thematically resonant within the broader context of your story.

By strategically implementing unexpected plot twists, you can heighten the stakes and enrich the reading experience, fostering a sense of anticipation and suspense that compels readers to remain immersed in your story until its gripping conclusion.

Use Examples: Offering examples of desired outputs can guide the AI towards the intended format or style (Reynders et al., 2022). For instance, if requesting a poem, providing a sample poem structure can steer the AI's creative process. Examples also help clarify ambiguous or open-ended prompts.

Break Down Complex Tasks: AI assistants excel at tackling well-defined tasks but may struggle with overly broad or complicated prompts. Breaking down a complex task into smaller, more specific steps can improve the quality of responses (Zhou et al., 2022). For example, when asking for a literature review, first request an outline, then prompt for each section separately.

Provide Constraints and Criteria: Clearly specifying constraints, such as word count limits or stylistic preferences, can help the AI tailor its output more effectively. Articulating evaluation criteria, like prioritizing factual accuracy or readability, can also enhance the relevance of the AI's responses (Stiennon et al., 2020).

Encourage Clarity and Coherence: AI systems may sometimes generate nonsensical or inconsistent outputs. Prompting the AI to prioritize clarity, logical flow, and coherence throughout its responses can improve the overall quality (Holtzman et al., 2020). Requesting that the AI double-check its work or rephrase confusing parts can also be beneficial.

By following these prompting strategies, users can more effectively communicate their needs to AI assistants, increasing the chances of receiving high-quality, relevant, and coherent outputs.

Asking the Right Questions

Below you will learn how to ask the right questions to unlock endless possibilities and propel us toward a brighter future. By mastering the art of prompt engineering, we can harness the power of inquiry to drive innovation, solve problems, and enrich our lives. Whether in business, education, or everyday interactions, the ability to ask insightful questions is a fundamental aspect of human intelligence and creativity. As we navigate the complexities of the digital age, let us embrace the power of prompt engineering to shape a world where curiosity thrives, and possibilities abound.

Asking the right questions is a fundamental aspect of personal development, problem-solving, decision-making, and innovation. Here's why it's crucial in each of these aspects:

Personal Development

Clarity of Goals: Asking yourself questions about your aspirations, values, and interests helps clarify your goals and direction in life.

Self-Reflection: Questions about your strengths, weaknesses, and areas for growth facilitate self-reflection and personal growth.

Learning and Growth: Curiosity-driven questions foster a mindset of continuous learning and development, leading to personal and professional growth.

Self-Reflection Prompts

Prompt engineering can facilitate personal development by providing individuals with prompts that encourage self-reflection, goal-setting, and introspection. For example, prompts such as "What are my strengths and how can I leverage them?" or "What habits do I need to cultivate for personal growth?" can prompt individuals to engage in constructive self-assessment and goal-setting.

Problem-Solving

Understanding the Problem: Asking probing questions helps to fully understand the problem at hand, including its root causes and underlying complexities.

Generating Ideas: Questions can stimulate creativity and generate diverse ideas for potential solutions to a problem.

Evaluating Options: Thoughtful questioning aids in evaluating different options and determining the most effective course of action.

Iterative Improvement: Continuously asking questions throughout the problem-solving process allows for iterative improvement and refinement of solutions.

Clarifying Problem Statements

Effective prompt engineering involves crafting prompts that help clarify problem statements and identify relevant factors to consider. By asking targeted questions such as "What are the key challenges we are facing?" or "What are the underlying causes of this issue?" prompt engineers can guide problem-solving efforts in a focused and systematic manner.

Decision-Making

Gathering Information: Questions help gather relevant information and perspectives necessary for making informed decisions.

Exploring Consequences: Anticipating the potential consequences of different decisions through questioning enables more thoughtful and strategic decision-making.

Aligning with Values: Questions that probe alignment with personal values and long-term objectives aid in making decisions consistent with one's principles and aspirations.

Decision-Support Prompts

Prompt engineering can aid decision-making by providing decision-support prompts that prompt individuals to consider relevant factors, weigh options, and anticipate consequences. For instance, prompts such as "What are the potential risks and benefits of each option?" or "How does this decision align with our long-term goals?" can help individuals make more informed and strategic decisions.

Innovation

Challenging Assumptions: Questions that challenge existing assumptions and conventional wisdom are essential for fostering innovation and thinking outside the box.

Identifying Opportunities: Curiosity-driven questions uncover new opportunities and areas for innovation by exploring unmet needs and emerging trends.

Encouraging Collaboration: Questions that encourage collaboration and diverse perspectives foster a culture of innovation within teams and organizations.

Iterative Experimentation: Asking questions throughout the innovation process facilitates iterative experimentation, rapid prototyping, and learning from failures.

Creativity-Stimulating Prompts

Prompt engineering plays a crucial role in fostering innovation by providing prompts that stimulate creativity, challenge assumptions, and inspire new ideas. By asking thought-provoking questions such as "How might we approach this problem differently?" or "What opportunities are emerging in this rapidly changing landscape?" prompt engineers can spark innovative thinking and problem-solving.

Prompt engineering serves as a strategic tool for guiding and shaping thinking processes in various domains. By crafting well-designed prompts that prompt individuals to ask the right questions, prompt engineers can facilitate personal development, enhance problem-solving capabilities, support decision-making, and foster innovation.

In summary, asking the right questions is foundational to personal growth, problem-solving, decision-making, and innovation. It fosters clarity, creativity, informed decision-making, and continuous improvement, ultimately driving success and progress in various aspects of life.

Understanding the Art of Asking

• Explore the psychology behind asking questions.

• Discuss the different types of questions (open-ended, closed-ended, probing, etc.) and when to use them.

• Provide examples of effective questioning techniques.

The Role of Technology in Prompt Engineering

• Examine how technology, particularly AI and natural language processing, is shaping the way we ask and answer questions.

• Discuss the potential benefits and challenges of using technology to enhance prompt engineering.

Applications in Business and Innovation

• Explore how prompt engineering can drive innovation and problem-solving in business contexts.

• Discuss case studies of companies that have effectively utilized prompt engineering to improve processes, products, and customer experiences.

Prompt Engineering in Education and Learning

• Investigate the role of prompt engineering in education and skill development.

• Discuss how educators can design prompts to facilitate critical thinking, creativity, and knowledge retention among students.

Ethical Considerations and Challenges

• Address ethical concerns related to prompt engineering, such as privacy, bias, and manipulation.

• Discuss strategies for ensuring transparency, fairness, and accountability in prompting AI technologies.

Practical Strategies for Effective Prompt Engineering

• Provide practical tips and techniques for crafting and using prompts effectively in various contexts.

• Offer exercises and activities for readers to practice their prompt engineering skills.

The Future of Asking

• Speculate on future trends and developments in prompt engineering.

• Explore potential applications in healthcare, education, manufacturing, technology, supply chain logistics, governance, and personal assistants.

  Conclusion

  Prompting is a critical skill for harnessing the full potential of AI. By understanding the fundamentals of prompting, types of prompts, and best practices for crafting effective prompts, individuals can unlock AI's capabilities and drive innovation. As AI continues to evolve, the art of prompting will become increasingly important for maximizing its benefits. By embracing the Socratic method, we can refine our approach to prompting and uncover new insights from AI. Looking ahead, the future of prompt engineering is both exciting and uncertain. As technology continues to evolve, new opportunities and challenges will emerge. From personalized learning experiences to AI-powered virtual assistants, the possibilities are endless. However, it's essential to remain vigilant and proactive in addressing ethical concerns and ensuring that prompt engineering serves the greater good.

References

Bolukbasi, T., Salman, M., & Kenton, Z. (2016). Man is to computer programmer as woman is to homemaker? Debiasing word embeddings. In Advances in Neural Information Processing Systems (pp. 4349-4357).

Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., ... & Hellen, C. (2021). On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258.

Gao, X., Yang, Y., & Li, X. (2021). A survey on prompt engineering for language models. IEEE Transactions on Neural Networks and Learning Systems, 32(1), 201-214.

Holtzman, A., Buys, J., Du, L., Forbes, M., & Choi, Y. (2020). The curious case of neural text degeneration. arXiv preprint arXiv:1904.09751.

Hovy, E., Yang, Y., & Li, X. (2021). Prompt engineering: A review of the literature. Natural Language Engineering, 27(3), 349-364.

Kurzweil, R. (2005). The singularity is near: When humans transcend biology. Penguin.

Reynders, G., Bianchi, F., & Haagsma, H. (2022). Improving sample-efficiency in language models with prompts. arXiv preprint arXiv:2205.06896.

Stiennon, N., Ouyang, L., Ziegler, J., Byrne, R., Voss, C., & Rurhmann, S. (2020). Learning to summarize from human feedback. arXiv preprint arXiv:2009.01325.

Socrates. (380 BCE). The Apology. Translated by B. Jowett.

Ye, D., Ji, Y., Sun, X., Ye, X., Zhang, X., Yin, J., ... & Luo, Y. (2023). Better prompting with Retrieval Augmented Language Models. arXiv preprint arXiv:2302.14229.

Zhou, W., Zheng, C., Cui, W., Zhang, H., Wang, Y., Hu, J., & Li, S. (2022). One prompt to rule them all: Pretraining soft prompts makes multi-task learning easier. arXiv preprint arXiv:2209.01367.