What do you do if AI skeptics are resistant to understanding the benefits of artificial intelligence?

The implementation of AI has to be positioned with a clear use case and with a clear understanding that there are risks involved that need to be identified and managed. Listening, is key to identifying and interpreting risks. Speaking from a clinical perspective, its much like proceeding with surgery, there are risks that need to be explained clearly and thoroughly and be part of the analysis of the purpose and desired outcome. Listening to the patient is a critical part of risk management. Taking such an approach is the way to build trust with those who are rightly skeptical.

Start by acknowledging their concerns about AI. Perhaps they worry about job displacement or misuse of technology. Validate their anxieties and then bridge the gap by highlighting how AI can augment human capabilities, not replace them.

Step 1. Position Ai as Augmented Intelligence. When it’s positioned as an enhancement to Human Inspiration it takes the scary away.

Understand where the AI skepticism is emanating from - previous failed initiatives or non applicability of use case in specific industry or issue of not looking with right lens. Address the concern with facts and data and help come up with use case with ROI - and help build crawl, walk, run for AI adoption

Before trying to convince someone of the benefits of AI, it is important to listen to their concerns and understand where they are coming from. By actively listening, you can gain a better understanding of their perspective and tailor your response to address their specific worries.

Para transformar céticos em defensores da inteligência artificial, que tal um desafio prático? Imagine convidar os céticos para participar de um "hackathon" de AI, onde eles possam colaborar diretamente na cria??o de solu??es simples que abordem problemas reais em suas vidas diárias ou em suas comunidades. Este envolvimento direto n?o só permite que eles vejam a tecnologia em a??o, mas também os torna parte da cria??o de solu??es, diluindo o medo do desconhecido e destacando a acessibilidade da AI. Ao transformar teoria em prática, mudamos a percep??o da AI de uma amea?a distante para uma ferramenta tangível e benéfica. A chave aqui é a experiência imersiva que real?a tanto a utilidade quanto a necessidade da tecnologia em nosso cotidiano.

Frame AI as a tool, not a threat. People fear the unknown. Emphasize that AI is a tool created and controlled by humans. We can set guardrails and ensure AI development aligns with ethical principles, prioritizing human well-being

Many AI skeptics are resistant to the technology due to fears of job loss, privacy concerns, and the potential for misuse. It is important to address these fears head-on and provide reassurance that these issues are being taken seriously and addressed by the industry.

Skepticism towards AI is understandable. Start by listening to their worries, be it job displacement, privacy, or ethics. Acknowledge the complexities of AI and avoid technical jargon. Focus on relatable examples: AI in medicine, safer driving, or environmental protection. Address their fears directly. Discuss safeguards in place for responsible AI development and the importance of transparency. This fosters trust and opens the way for a productive discussion about AI's potential to improve our lives.

Primero, hay que admitir lo siguiente: Sí, la IA puede ser intimidante. Y sí, también tiene el potencial de cambiar radicalmente cómo trabajamos, vivimos y nos relacionamos. Pero, ?acaso no es eso lo que también prometían el teléfono, el internet y hasta la electricidad en sus tiempos? Para aquellos que temen ser reemplazados por la IA, sería útil recordar que la tecnología, mientras transforma empleos, también crea nuevos empleos. Por otro lado, muchos de estos temores vienen de ideas un tanto exageradas sobre lo que la IA puede hacer, por lo que enfocarse en la educación es clave. Cuanto más sepan las personas sobre cómo funciona realmente la IA y cómo se implementa, menos parecerá una caja negra de magia vudú tecnológica.

In my own interactions with companies, I've noticed a clear trend: skepticism in the workplace often stems from two main fears. First, employees worry that AI might replace them. Second, employers have significant privacy concerns. To address privacy worries, it's crucial to use tools and services that comply with privacy standards. Custom solutions tend to foster greater trust among managers. As for the fear of replacement, it's a human reaction. To mitigate this, AI specialists and company leaders need to be transparent and communicative about the intended uses of AI. Fear tends to spike when managers roll out new technologies without prior discussion or clear explanation of the benefits.

Make AI relatable, not intimidating. Don't just talk about complex algorithms. Show them how AI is already being used in their daily lives: facial recognition unlocking their phone, AI-powered recommendations on streaming services, or even spam filtering in their email. Highlight the positive impact of this technology they already use

More than share success - be specific to use cases and share a path of success with ability to try a specific use case, with clear success metrics

What works for me is sharing stories of big companies that have implemented AI and seen an increase in profit. There are countless case studies out there and you can surely find one for your use case. These big corporations are leading the way in AI adoption, so explaining to your listener that AI is inevitable is a great way to get them over the line Make sure to talk in their language, focusing on tangible benefits rather than technical jargon

Success can be considered in many different forms. It is therefore essential at the outset to clearly define with stakeholders and business owners what success looks like (reduced costs, task completion speed, accuracy of forecast, levels of customer satisfaction etc) and identify the key benchmark data required to validate the solution and also the cost and resources to determine the business case to scale any initial proof of concept or pilot.

Highlighting successful AI implementations can help to demonstrate the potential benefits of the technology. Share stories of how AI is being used to improve efficiency, accuracy, and safety in various industries.

Spark a conversation, not a lecture. Don't talk at them, talk with them. Ask questions about their interests and then show how AI can be a tool to explore those passions further. Maybe an AI art generator could inspire a new creative outlet, or perhaps an AI-powered research assistant could help them delve deeper into a topic they're fascinated by.

After addressing concerns, spark curiosity! Don't force information. Instead, suggest resources or communities where they can explore AI at their own pace. Offer to answer questions and discuss topics of interest. By fostering a sense of exploration, you empower them to learn and form their own informed opinions about AI's potential.

Fomentar la curiosidad en un campo tan amplio y, a veces, incomprensible como la IA puede ser algo súper divertido. Lo primero, es pedirle al equipo que tengan la mente abierta, ya que detrás de esos algoritmos y modelos estadísticos, hay personas. Personas que cometen errores, incluso al momento de desarrollar estas aplicaciones tan poderosas. Segundo, demosles algo con qué jugar. ?Qué tal un peque?o proyecto de IA que puedan manipular ellos mismos? Al momento de hacerlo es importante que cada persona note los cambios, y esto servirá de estímulo para continuar. Y, por último, impulsemos a que ellos mismos se pregunten qué problemas de su día a día podrían solucionar con la IA.

Frame AI as a collaborative journey, not a one-sided solution. Don't present AI as a finished product with all the answers. Discuss the ongoing development and ethical considerations. Encourage open dialogue about the future of AI and how it can be shaped responsibly for the benefit of all

For AI to be successful in an initiative, the tool relies on feedback and iteration from a diverse team. Once you've represented the problem clearly, and AI is shown to prove valuable from a prototype, it is important to address concerns across the organization. These could be legal, privacy, HR or product stakeholders that may want to ensure the functionality is representative of the businesses' goals as whole.

Keep the conversation going by promoting a two-way dialogue. Invite them to share their thoughts and questions, and be ready to respond with thoughtful answers. This ongoing exchange can gradually shift perceptions as they become more familiar with AI.

AI is a capability and commercial tool with the integration of MS Co-pilot into many organisations which should deliver substantial value if everyone in the company is suitably trained and receptive to leveraging the benefits it can deliver. As a new technology, the companies that will extract the most value for their business are those who invest in their employees training and upskilling. This will require a defined programme of core modules for all employees and a more specific training for those in different business units. Given the nature of the technology such training should be delivered from a Centre of Excellence (CoE) in large Enterprise companies and be shaped by people with practical AI experience gained in the real world.

In science, unlike in dogmatic beliefs, the more you question, the better the results. Imagine a world without skepticism, where every statement is taken for granted, doubts are never raised, and questions are left unasked. How could such a world improve, bound by its own limitations and unchallengeable truths? Be grateful that AI and other innovations are met with caution. This means you will think more deeply about the subject, consider questions you had never asked yourself, communicate with social context in mind, notice previously overlooked points, and be better prepared for risk mitigation. Ultimately, the world benefits more from something that truly sparks interest, fear, curiosity, and, eventually, proof-based acceptance.

In my experience of safety critical sectors, advanced technology is adopted with much excitement and fanfare but with little or no safeguards (e.g. patient safety; cybersecurity). This creates a recipe for disaster which ultimately sets back long term technology adoption. For AI it's clear that project managers and suppliers need to demonstrate they are proactively complying with new global risk management standards such as ISO42001 and legislation such as the EU AI Act. These are critical steps for building trust.

I would prepare a video for a scenario of an GPT-Assistant with loom. How to do/creat a GPT, How it works, results and how to use it in their company. Be sure, they will be positive surprised...

Be aware of the ethical implications of AI and be prepared to discuss them. Be transparent about how the AI system works and what data it uses Be open to regulation and oversight Be aware of the potential for bias in AI systems and take steps to mitigate it Be prepared to address the potential for job displacement and take steps to retrain and upskill workers.