How do you educate yourself and others on AI in finance?

Attend conferences Prioritize attending industry-leading AI conferences. Many prominent AI and ML conferences dedicate special days or tracks to AI in finance, featuring workshops, invited talks, tutorials, and poster sessions led by both academic and industry experts. These events provide a unique opportunity to stay updated on cutting-edge research within this domain. Moreover, attending these conferences enables you to build a valuable network of professionals actively involved in AI applications in finance. I highly recommend attending conferences like NeurIPS, ICML, ICLR, AAAI, IJCAI, KDD, WSDM, and WWW. They offer unparalleled insights and connections that can significantly enhance one's expertise in AI within the financial sector.

I published a book "Rise of The AiCCOUNTAnTS?: The What, Why, and How of AI for Accountants." While it was written for accountants, it is a guide for anyone learning about AI. Here are the core recommendations from the book that I belive should be your AI learning roadmap: 1. Learn how AI tools are created (you don't need to be a technologist to understand it) 2. Learn how AI itself learns (on its own) 3. Learn how AI works. Once you have this core foundational understanding, you can easily grasp any AI tool you will likely use in your work. Learn

Conferences and in-person meet-ups are highly valuable in this field. Meeting others and networking will offer more insights and experiences than one book or blog at a time. We attended the Fintech for good conference earlier this year and took away a lot of food for thought and action points for exploration

To educate yourself and others on AI in finance, you can follow these tips: 1. Stay updated with the latest news and research: Follow reputable sources such as industry publications, academic journals, and technology news websites to stay informed about the latest developments, applications, and trends in AI in finance. This will help you stay up-to-date with cutting-edge technologies and advancements.

Having a project and marrying it with curiosity is the best way to understand the specific skills and knowledge you need to develop. General online courses are extremely helpful for teaching out a wide, though oftentimes shallow skill-set. Once you have the bearing of the basics, you need to start attempting to apply it in your own work. Go out and use some of the existing tools that seem interesting to you and use them to better understand their value. As you keep doing this you'll create an arsenal of effective tools that can be applied regardless of the challenge.

2. Engage in online courses and educational programs: Enroll in online courses, webinars, or educational programs specifically focused on AI in finance. Platforms like Coursera, edX, and Udacity offer courses on various AI topics, including their applications in finance. These courses can provide structured learning and help you gain in-depth knowledge. 3. Join professional communities: Engage with professionals, researchers, and enthusiasts in the field of AI in finance by joining relevant online communities, forums, and social media groups. Participate in discussions, ask questions, and share your insights. This will help you learn from others, exchange ideas, and stay connected with the latest discussions.

There are some great AI communities online, including on LinkedIn. I really like Facebook groups for this too. 'ChatGPT & AI for Accounting' as an example

4. Attend conferences and events: Attend conferences, workshops, and seminars related to AI in finance. These events bring together experts and leaders in the field, providing opportunities to learn from their experiences, listen to keynote speeches, and network with industry professionals. Stay updated with event announcements and consider presenting your own research or insights if possible. 5. Read books and research papers: Explore books and research papers that delve into the applications of AI in finance. Books written by industry experts or academics can provide comprehensive knowledge on the subject. Research papers published in reputable journals can offer insights into the latest advancements and methodologies.

As AI is now exploding and there still aren't solidified "best practices" in many areas, it's a phenomenal time to experiment yourself and share your findings with the wider community. Test the tools out yourself against common challenges to showcase how effective they might be. This will help cement you as a thought leader in the space, while simultaneously bolstering your own skillset and knowledge-base.

Sharing is caring. We are all learning and discovering as we go, and sharing those learnings and insights with our colleagues will help the sector. Think about your company blog as a place to share these, or share them in closed online communities so you can seek feedback and other perspectives

Once you have gained a foundational understanding of AI, there is no better way to deepen your AI expertise than experimenting with AI tools and collaborating with AI creators and users in your industry. As a starting point, don't start with any tool. Start with what your clients want/need and how you can deliver better impact by using an AI tool (impact, which is not easy to produce without using an AI tool).

6. Create educational content: Share your knowledge and insights by creating educational content. Start a blog, write articles, or contribute to AI and finance publications. Explain complex concepts, provide use cases, and discuss the impact of AI on various aspects of finance. By sharing your expertise, you can contribute to the education of others and foster discussions within the community.

Before you start your career in AI, you should have a solid foundation in software engineering and the programming language of your choice, preferably Python. This is a crucial step that is often overlooked by many aspiring AI developers. Most of the successful AI professionals I know have a strong background in software engineering.

Use Large Language Models and other tools such as chatGPT and perplexity.ai to deconstruct the narratives when you make investment decisions. Investment decisions are driven by an "investment case", which is a story. Don't get married to the story. To look for the alternative views you can use AI very efficiently. Manage your conviction level to the sweet spot, which is 6-7 out of 10. Not too hot, not too cold.