Responsible AI: Balancing Innovation and Ethics with Temi Odesanya
In this enlightening discussion, Cassi Jones engages with the esteemed Temi Odesanya, a distinguished technology professional renowned for her expertise in automation, machine learning, and responsible AI. The conversation delves into the imperative role of women in technology, emphasizing the transformative potential of artificial intelligence in democratizing data and enhancing business intelligence.
Temi articulates the dual nature of AI, highlighting both its unprecedented opportunities and the ethical considerations that accompany its implementation. Drawing from her extensive experience, she elucidates the challenges organizations face in adopting AI technologies responsibly, advocating for a thoughtful approach to integration.
This episode is a profound exploration of the intersection between technology and ethics, offering invaluable insights for professionals navigating the evolving landscape of AI.
Key Takeaways:
- The podcast emphasizes the significance of increasing female representation in the technology sector, aiming to empower women through shared stories and experiences.
- Cassi articulates her commitment to community engagement and mentorship while highlighting her professional journey as an Information Security Analyst.
- Temi discusses her extensive expertise in AI and automation, emphasizing the need for responsible AI practices within organizations.
- The conversation explores the dual nature of AI technologies, recognizing both their transformative potential and the ethical challenges they present to society.
- Listeners are encouraged to consider the implications of AI on job displacement, underscoring the importance of upskilling and adaptability in the evolving job market.
- Temi's insights reveal how personal experiences shape professional journeys, advocating for mentorship and continuous learning as pivotal elements for success in technology.
Find them online:
Cassi Jones: https://www.linkedin.com/in/cassih/
Temi Odesanya: https://www.linkedin.com/in/temiloluwaodesanya/
Find us on Instagram:
https://www.instagram.com/witlovepodcast/
Transcript
Welcome to Whitlam, a podcast founded by women, produced by women about women in technology.
Speaker A:There is a huge place for women in tech and this podcast is going to get well into the work as a leading contributor to help change the trajectory and see the rise of women in technology.
Speaker A:Sit back and enjoy as our young female hosts share energy with experienced professional women in technology.
Speaker B:Welcome to the witlove Podcast, a podcast that is connecting young hosts like me to professional women in technology where we'll get to share wisdom and learn about each other in the process.
Speaker B:My name is Cassian Jones.
Speaker B:I am an Information Security Analyst and a B Math graduate from the University of Waterloo.
Speaker B:I am passionate about giving back to the community and have led several strategy, data and diversity initiatives for national and local organizations including TD Bank, Aspire, Motivate Canada and the Merit Award Bursary Program.
Speaker B:In my free time, I love participating in new fitness challenges and helping youth become more financially literate.
Speaker B:And now for the moment all of you viewers and myself has been waiting for, I am so thrilled to introduce Tammy Odessanya Temi is a seasoned technology professional known for her automation, machine learning and emerging technologies expertise.
Speaker B:As a responsible AI leader at aig, she is responsible for ensuring AI solutions align with responsible AI principles and standards.
Speaker B:She has led teams in strategic planning, execution and the launch of pioneering technologies including artificial intelligence, automation and Metaverse initiatives.
Speaker B:In addition to her dynamic corporate role, Temi is a dedicated part time professor imparting her profound knowledge in machine learning and responsible AI at various Canadian postgraduate institutions including Durham College, Conestoga College and Concordia University.
Speaker B:Beyond her professional endeavors, Temi exudes a passion for mentorship and career guidance.
Speaker B:She has coached many different professionals helping facilitate their attainment of mid to senior leadership roles.
Speaker B:Her commitment to education is complemented by her extensive academic background which includes a Master's of Science in Management in Business analytics from Ivy Business School Western University.
Speaker B:She also holds a Graduate Certificate in Salesforce and CRM analytics, but from Santa College and a Bachelor's Degree in Management Information Systems from Covenant University.
Speaker B:I personally have the pleasure of seeing Tammy speak and oh my gosh, from the moment I did I knew that she would be such a great guest to have on this podcast.
Speaker B:So Tammy, welcome to the show.
Speaker C:Thank you, thank you.
Speaker C:I was blushing as you're reading my bio because I'm like oh is that me?
Speaker B:It is and own the awesomeness that is you and we are going to spend a lot of time in this segment hearing about how awesome you are and learning from your expertise.
Speaker B:Well thank you so much for joining.
Speaker C:Thank you, Kathy, of course.
Speaker B:And to start off just for the audience to get to know you and for me to get to know you even more, we're going to start off with a couple warm up questions.
Speaker B:So if you could have dinner with any historical figure, who would it be and why.
Speaker C:Would I like to have dinner with?
Speaker C:Let me see.
Speaker C:Yeah, Actually thought about that, though.
Speaker C:Oh, I think it's gonna be.
Speaker C:This is cliche, but it's gonna be Esther in the Bible.
Speaker C:Queen Esther.
Speaker B:Love it.
Speaker B:Love it.
Speaker C:Yes.
Speaker C:And I would love to have dinner with her because if you read the Bible, it talks about a poise, elegance, a humility, and how she was a soft coin.
Speaker C:So just getting all of that, that is so fantastic.
Speaker B:And she is a fantastic role model.
Speaker B:I love that.
Speaker B:You know, I have a question.
Speaker B:If you could have any superpower, what would it be and how would you use it?
Speaker C:I think it's reading people's minds.
Speaker C:How would I use that?
Speaker C:I think I would.
Speaker C:I will learn how to convince people and influence them and also know when to disappear from there.
Speaker B:So I think that is so important because a lot of communication first starts with knowing and understanding your audience.
Speaker B:Right.
Speaker B:In order to do that, you have to step into, you know, their mind.
Speaker B:What are they thinking, what are they approaching this?
Speaker B:Right.
Speaker B:So you could.
Speaker B:Yeah, I feel like it would make, like presenting, curating content just so much easier.
Speaker C:Exactly.
Speaker C:And then, you know when they're about to say no and you can say the right things just to get a yes.
Speaker B:So thousand percent.
Speaker B:Fantastic.
Speaker B:So diving right in.
Speaker B:I would love to know what initially drew you to the world of AI and automation.
Speaker B:Was there a defining moment in your career that really sparked your interest?
Speaker C: been in the field for, since: Speaker C:And for me it was just reading books as well as.
Speaker C:So my family has, or I say my mom, she has an outdoor advertising business and there was a time where we flew to the Netherlands for training and part of that training was, which is now against privacy law, but back then it wasn't.
Speaker C:It was reading people's split number and being able to program the system to sing Happy Birthday, being able to understand what they like so you can advertise that on the electronic boards.
Speaker C:And that was one of the things that sparked my interest to go into analytics.
Speaker C:Back then.
Speaker C:It was business intelligence.
Speaker C:And I've grown in the field.
Speaker C:I found things I like, things I don't like.
Speaker C:Particularly responsible AI for me was getting misdiagnosed as well as being flagged for money laundering by the algorithm and I had to pay fines to my seller when I was trying to buy a place.
Speaker C:So it's, it's just been, you know, different things that have led me to continue the journey.
Speaker B:I think that is so fantastic.
Speaker B:And what I love about, when you were describing your story, you talked about this idea of like making a personal connection.
Speaker B:I think you mentioned the, like, the display, the happy birth.
Speaker B:And it's so fascinating because as we talk about AI and I think what has made technologies like ChatGPT very prominent is because they're able to facilitate that human connection.
Speaker B:So I absolutely love how that sparked your interest or that was kind of one of the defining moments in your journey.
Speaker B:But that actually lends itself very well to coming back that full circle in your AI journey.
Speaker B:So that's fantastic.
Speaker B:Thank you.
Speaker C:Thank you.
Speaker B:Of course.
Speaker B:So with the rise of generative AI technologies, what do you see as the most significant opportunities or maybe challenges for businesses that are adopting these tools?
Speaker C:It's both ways.
Speaker C:So as AI continues to mature, I don't think any organization is probably at its peak right now because you're sitting somewhere and somebody launches something like, oh my God, what is that?
Speaker C:And there's so many opportunities for organizations in democratizing data, helping the business understand insight itself.
Speaker C:So not just going by procedural way of doing things, but looking more at creative ways of working.
Speaker C:Going back to, from an HR perspective, being able to analyze all surveys and then come up with recommendations for the employees, which are then personalized.
Speaker C:But people have not been able to do that.
Speaker C:They just look at you as a group and then determine what that is for you.
Speaker C:The other way around is automation across different sectors and different business functions.
Speaker C:So being able to move data, get insight fast.
Speaker C:Now we're moving from being a data, employing a data analyst to being able to write those sentences and getting those insights directly without going to talk to a data team is another very beautiful way.
Speaker C:When it comes to movies, which I love, you can create movies.
Speaker C:Now you, well, you can create movies to a certain extent.
Speaker C:You still need the professionals.
Speaker C:But in all, it's just the augmented way of working that I'm excited about.
Speaker C:On a personal front, there are also, I would say, situations where I've been and I needed the advice of a coach.
Speaker C:Right.
Speaker C:So being able to leverage AI or ChatGPT or Claude and asking questions while giving me context has been very helpful for me to take steps.
Speaker C:But then human in love.
Speaker C:Also check in with my coach when she has time to say, hey, I did this I hope it's okay.
Speaker C:Here are the things that I've done.
Speaker C:On the other end of every advancement, there is always a consequence to it is the impact of AI in the society, from families to communities, on businesses.
Speaker C:Also from a regulatory approach and prohibited practices.
Speaker C:And also from an individualized aspect where whether we like it or not, it is everywhere.
Speaker C:It is embedded on every website and now people are using it for things that are prohibited.
Speaker C:And what makes it complex is you can't go by morals because what is acceptable to you is not necessarily acceptable to me.
Speaker C:So who makes the more compass of what AI is supposed to do and not supposed to do?
Speaker C:However, there is a general rule that we know people should not be harmed in the process.
Speaker C:So going back to what this consequences look like, it is being able to identify stereotypes in predictions.
Speaker C:Just like I was flagged things that don't make sense.
Speaker C:I wish I had such money to be flagged a money launderer, which I don't have.
Speaker C:Looking at the healthcare sector where now we're starting to see the lack of representation in health care data and that is what has been used to diagnose and treat people and we're starting to see how that is impacting us, impacting our lives right at the same time we're looking at copywriting.
Speaker C:So who's writing some of those articles?
Speaker C:Good story.
Speaker C:There was a popular Nigerian celebrity that got married and I put it on big, just asking questions who the person was.
Speaker B:I knew who she was, but I.
Speaker C:Just wanted to see what was out there.
Speaker C:And the AI gave me misinterpretation and misinformation saying the lady had been married and she had kids, which is obviously not true.
Speaker C:So we're starting to see how misinformation has been ported and how that context and that content is being used to now make decisions that people are not even fact checking itself.
Speaker C:So it's both a scary time, an exciting time and we're just waiting to see where the path leads us to.
Speaker B:I think there's so many great points that you've brought up in that and you're absolutely right.
Speaker B:Like with any technology it really is a double edged sword and innovation often is.
Speaker B:And it's similarly to the Internet.
Speaker B:Right.
Speaker B:Like before it started it was like, okay, it was this new emerging thing, there's so many opportunities.
Speaker B:But now it's like you have, you know, the plethora of good, but you also have, you know, significant potential for misuse.
Speaker B:I'm personally in cybersecurity and because Internet usage has expanded so much over the past couple of years, the ways in which information can be compromised is also increased just as much.
Speaker B:So there really is that, you know, those positive benefits and then there's also those consequences.
Speaker B:And it's really critical to keep that both in mind for all audiences, from the end user all the way up to organizations that are considering implementing AI initiatives.
Speaker B:So I want to actually zero in on that and talk or understand a little bit more about kind of the process of, you know, organizations are seeing this as an opportunity.
Speaker B:They're seeing how much value it could add to their workforce.
Speaker B:But what are some common pitfalls that organizations face when they move on to the implementation stage, and how can they ensure that as they work to implement or integrate AI solutions, that they do so ethically and responsibly?
Speaker C:Yeah, that's a good question.
Speaker C:I think I get asked that all the time regarding the pitfalls.
Speaker C:Anyone can fall into it like it's not.
Speaker C:You just have to keep striving to check all the boxes.
Speaker C:So some common examples are one, not defining the right problem.
Speaker C:And this goes back to the basics of business itself.
Speaker C:It's not even about the technology.
Speaker C:What am I trying to solve for?
Speaker C:It is going beyond using AI as a tool to using AI as an enabler, which is enabling whatever use case you have, not just selling AI.
Speaker C:And as we know, when there's investment, there has to be rewards on the investment.
Speaker C:And so sometimes organizations or leaders in organizations don't have the patience to wait to ensure all those boxes are checked because they need to provide value back to their needs, shareholders.
Speaker C:As a result, people don't define the problem and then they run into it.
Speaker C:Sometimes you define a problem and you get into the data exploration phase and you realize that you don't have enough data, or you have data, but you have legal restrictions that prevent you from using the data.
Speaker C:So what do you do?
Speaker C:You got, you've signed all those contracts with vendors, you've gotten buy in, you need to do something.
Speaker C:So then people proceed to using whatever they have.
Speaker C:Either it's the right data or they use the right data, but not with the right permission.
Speaker C:And in the development stage, this is where, you know, sometimes communication gets lost in translation.
Speaker C:The business person might not have necessarily explained the process well, or maybe they did to the technical person, but that gap is still missing.
Speaker C:And so assumptions are made that are incorrect.
Speaker C:And so you develop the wrong model.
Speaker C:But let's say all well and good, everything is solid, you develop the right models.
Speaker C:When it comes to deployment, sometimes you might actually deploy in the wrong market.
Speaker C:So good use case, the world is not just ready for it.
Speaker C:It doesn't kick off, things go a wire, things go missing.
Speaker C:All the other flip side is something went wrong because especially with gen AI use cases, there are different components.
Speaker C:It's not just the model, it is the platform that is hosting the model.
Speaker C:You know the integration mechanisms that needs to be present and you might find out that probably the platform can carry it.
Speaker C:The platform doesn't have the required configuration for that.
Speaker C:Now all well and good, you check all the boxes, you deploy it, something happens to the economy.
Speaker C:What was trending isn't trending again.
Speaker C:So I'll give an example.
Speaker C:During COVID the retail market changed.
Speaker C:Right before people loved going to fiscal stores, but then people couldn't go to fiscal stores because of all the issues that were happening.
Speaker C:Brick and mortar stores needed to go online.
Speaker C:So imagine if you had developed a model and it had predicted market demands or the purchases that were going to happen.
Speaker C:Covid struck.
Speaker C:Your model is drifting.
Speaker C:It's not giving the right, it's not the ground truth, which is the exact data is exactly not what the model is predicted.
Speaker C:And you have to take it back and retrain it.
Speaker C:But what are you retraining on?
Speaker C:Because so many things are shifting in the market.
Speaker C:So that's also another P4 that sometimes is uncontrollable, but you just have to take the lens, take the model off and retrain that and you know, possibly you did it right.
Speaker C:It's in the right jurisdiction.
Speaker C:Everything is playing well.
Speaker C:Post deployment a new regulation comes out and what was good or what was acceptable is no more acceptable.
Speaker C:And you have to keep on top of that.
Speaker C:And this is where multi stakeholder, multi stakeholder collaboration is required.
Speaker C:So you actually need business people, compliance, security, which is very crucial at this moment.
Speaker C:You need the financial team like you need everybody's hand on deck.
Speaker C:Pre deployment, post deployments we would do that.
Speaker C:And once it comes to the ethical use of AI, like I said at the beginning, we can go by morals.
Speaker C:And many people approach responsible AI from a policy angle which is here is the procedures you should follow when doing X, your body is acceptable.
Speaker C:However, we fail to realize that the human mind doesn't stop.
Speaker C:We're always so creative and sometimes the policy doesn't address the creativity at that moment because people are doing different things.
Speaker C:So now it goes beyond just having a document to putting all we talk about guardrails, but putting the required guardros at each step of the life cycle without also strangling the developers or strangling the technical teams, which is very hard to do because this is where companies have to decide what is acceptable to them in the use of AI, what are they comfortable with and what is the boundaries they don't want to go past.
Speaker C:What is the regulation asking for, what are their shareholders asking for, whether the employees are asking for.
Speaker C:And then determine the type of risk they can take based on that.
Speaker C:It's now craft out all the controls that will go in at each stage of the life cycle, ensuring that they can automate as much as possible.
Speaker C:Because sometimes I remember, you know, I developed this process, beautiful process.
Speaker C:I was so proud when it was my turn to go through that process and I had to read like 10 different documents.
Speaker C:I'm like, hell no, I have to find a better way to do this.
Speaker C:Right.
Speaker C:And so that's where automation comes into place, where, you know, you're, you're moving data from one point to another, you're having the right monitoring, you're having the right governance in place.
Speaker C:You're carrying everything, accept everything that is required.
Speaker C:However, you're doing it on a risk based factor.
Speaker C:What does that mean?
Speaker C:If I have to build something that has very low risk, like gadget information, it is different from if I have to use facial recognition for a task.
Speaker C:Now I always use this analogy where facial recognition in Nigeria, no one really bruises their brows if it's used by a random company.
Speaker C:However, if I'm in Europe, somebody will raise their brow.
Speaker C:So it's understanding what exactly is acceptable for the jurisdiction of where I'm developing this, what is my comfort level with the risk of it and what is actually acceptable to me as a human being.
Speaker C:Blending all that together while working with the people in the academics, the people in the industry, the vendors that you have going for conferences so that you can be on top of your game and know when to pivot and when to adjust.
Speaker C:It was a long spiel by the end of the day, do no harm.
Speaker B:A fantastic spiel.
Speaker B:I loved so much of that.
Speaker B:And the first thing that comes to mind is, you know, we have the silicon model valley of like move fast, break things.
Speaker B:But I think one is really like a hedge to that is to be very thoughtful about who you have in the room when you're actually going through the process of developing this and then also thinking about risk and really thinking about that thoughtfully, strategically and at the beginning.
Speaker B:Yes.
Speaker B:Which is so incredible because as you were saying, your answer, what came to mind is I work in finance and we often there's there's kind of this notion in finance that like, oh, we can predict the future.
Speaker B:Like, we can, you know, the stocks will go up into the right continuously.
Speaker C:They met Trump.
Speaker C:Things are changing.
Speaker B:Also a great example, like one of my favorite books is the Psychology of Money.
Speaker B:And they talk about this idea that like, we spend so much time like looking in the past.
Speaker C:Yeah.
Speaker B:But it's like the future is so uncertain and so much happens, especially from an economic perspective, is really driven by the like macroeconomic environment, which no one knows.
Speaker B:So I think, you know, thinking through that concept and thinking of like, how do we mitigate this with this technology that really is like agile and adaptive, like to adapt with it.
Speaker B:And that to your point, like starts with who's at the table, having the right people at the table, making sure that we build agility into the processes that we're developing and then also ensuring that, as you said, like, we're not.
Speaker B:We're striking that balance between building creative solutions, being creative, being able to take advantage of these opportunities, but also balancing that out with risk.
Speaker B:So I think that is so brilliant.
Speaker C:Yes.
Speaker B:And moving on to another question that almost ties into this.
Speaker B:So I imagine that because there's so much cross pollination between all the different departments that you have to work with for a given AI solution, how do you, what helps you ensure that when you're communicating that you're able to really stress and drive the value and kind of tailor that messaging to all the different people that you work with.
Speaker C:So it's a ever evolving process because one minute you're like, oh, I got this.
Speaker C:The next minute, oh my God, how do I get through this?
Speaker C:Some of the things that I'm doing, which I'm so looking for creative ways, is one, getting a coach who's great at executive leadership and communication.
Speaker C:I'm starting to take storytelling courses right now myself, being able to tell a good story.
Speaker C:The other thing is finding mentors in the field or just peers who are also writing and doing some of these things.
Speaker C:In all the one crucial characteristics that, you know, I, I look for and I'm also like working towards is being able to understand what's at stake for who I'm talking to.
Speaker C:So I realized that when I stepped back from trying to push my agenda, I go, okay, what does this person care about?
Speaker C:What will matter to them?
Speaker C:And then translating that into an impact for them.
Speaker C:So a good example is if I'm talking to a data science team and I'm like, hey, we need to roll out this model just like they need to roll out that model.
Speaker C:However, if I'm talking to the legal team, it is, we need to roll out this model to avoid, you know, maybe to ensure what compares with regulations.
Speaker C:So possibly an AI model that does monitoring something along that line.
Speaker C:That way people understand what is at stake for them.
Speaker C:Now the only thing that I find really important is having one on one with each of these leaders.
Speaker C:I understand what they're working on and so I can tell them how my own interest is a good vested interest for them.
Speaker C:And that way I could use my relationships.
Speaker C:And this is something like my boss currently encourages me to do.
Speaker C:And I continue to do it and I've seen it work.
Speaker C:So the other thing too is reading about the technical concepts and then saying like, if, if you can't grasp it sometimes, like explains me like I'm five and he does that for me.
Speaker C:And then I'm able to then tie that back to what I have to do.
Speaker C:But again, the audience is different.
Speaker C:The audience will keep changing.
Speaker C:What regulators want or expect to hear is different from what my senior leadership expects to hear, which is also different from what the employee expects to hear.
Speaker C:So it's been another thing that, that, that I feel is very crucial is being able to detach from myself, which is the hardest thing ever.
Speaker C:Because you hear this thing like, smart people feel like everybody knows what they're talking about.
Speaker C:And I find myself going, going into such poor.
Speaker C:And I'm like, okay, tell me, step back, step back, step back.
Speaker C:So being able to step back and then tell myself that imagine you are talking to yourself like you don't know what it is.
Speaker C:Always give context.
Speaker C:So that's something that really helped me.
Speaker B:I think that's such brilliant advice and speaks to the very first thing we're talking about with the kind of the role of the human connection.
Speaker B:Right.
Speaker B:I love the idea that, you know, you mentioned that you have one on ones and everything.
Speaker B:And something else that you mentioned that really stood out for me was that, you know, you have to first start by defining the problem.
Speaker B:Right.
Speaker B:But if you don't know what, you know, the perspective of the people who have the problem, like what they're coming into it with, what outcomes they want to see, even they see, or like what success looks like, then you're never going to be able to create a solution that really delivers the impact that they're looking for.
Speaker B:Really, really critical.
Speaker B:And for anyone in technology, I think one, one area of focus that we often have to do is like, how do we tailor that message to People who literally have no idea, none at all, what we're talking about.
Speaker B:And then how do we tailor that message again to really deliver that impact?
Speaker B:So that's a really key skill to be able to have to be effective in that role.
Speaker C:How about you though?
Speaker C:I always like to learn from people.
Speaker C:What has helped you in tailoring your message?
Speaker B:Yeah, very, very great question.
Speaker B:So one, I, as much as I can present, I presented to people who are like not in my field, have like no idea what I'm talking about.
Speaker B:Like my husband, he's chef by nature, so by trade and he's not in technology.
Speaker B:So like I explain it to him and if he can get it, then I'm like, okay, not a good one.
Speaker B:He's, he's brilliant.
Speaker B:I love him very dearly because, you know, there's so many acronyms and you can get so yeah and like so in the weeds that like you wait litmus check to say, okay, like am I staying high level enough?
Speaker B:Am I making it personal enough so that someone with.
Speaker B:Yes, exactly.
Speaker B:I agree, I agree, that definitely helps.
Speaker B:And then also my little sister, who, she's an interior designer, she's a fantastic artist, same thing as well.
Speaker B:Like, and she's like, I don't care about technology.
Speaker B:Like I just, I just want the end product and I'll use it.
Speaker B:Like I don't care about how it works.
Speaker C:I love interior designs.
Speaker C:Like sometimes I'm just on my phone, crazy design with AI and like I wish I had so much for it and this would be my house.
Speaker C:So.
Speaker B:So yes, talking to people outside of your field is very helpful.
Speaker B:Amazing.
Speaker B:So I am so excited by this conversation we're having, but I'm sure there's many of our viewers that are interested in the field of AI.
Speaker B:So how should professionals across non technical fields prepare themselves to work alongside AI or with AI enhanced environments?
Speaker C:So I break that down into two categories.
Speaker C:So one is the producers of AI and the other is the consumers of AI.
Speaker C:So if you're producing AI, it possibly you're in a technical role or you're in a functional role, which means that you work with the technical team and the business team to produce something that has AI as a product or as a service that you want to sell in that I would say continue to learn, continue to study.
Speaker C:What you know, yesterday might not be relevant today, which is the most painful part of the field, but it's also the most exciting part of the field because you're not bored at all.
Speaker C:Talking to people, you know, going to conferences but also taking certifications, however, taking certifications to what is required in the market.
Speaker C:So there's a role that were very popular three, four years ago.
Speaker C: were so many privacy jobs in: Speaker C:Right now there's still privacy jobs, but the number is reduced and it's now, it's now evolving into AI governance roles.
Speaker C:So as you can see, there's still privacy rules, don't get me wrong.
Speaker C:But the more added responsibilities to such roles and it's sprung into a separate new role.
Speaker C:So this is where people have to be on top of their game if they're in the field.
Speaker C:For consumers of of AI, this is understanding what exactly it is.
Speaker C:And the easiest way to start is to start with something that you love.
Speaker C:So it might be a hobby, it might be an area of interest where you pick a pre built tool which is the tool that has been built for you that has AI in it.
Speaker C:Don't try to build one yourself yet, just understand it and then try to learn how it can be used in your job, in your personal life.
Speaker C:I use it for groceries.
Speaker C:I have nutritional or I have a diet that I like to follow, but I also don't want it boring because I don't like to eat rice twice in a week.
Speaker C:So I try to let me know I I don't like to eat the same type of rice twice in a week.
Speaker C:So if I have to eat Jollof rice today, I eat fried rice in the next three days but not tomorrow.
Speaker C:But anyway, so trying to use it to come up with my own diet myself, I also use it spongebob to interpret some of my own results like I use it to read okay, you know, maybe my fitness score came back as X and try to understand Y minus X.
Speaker C:Right?
Speaker C:So starting with something that is of interest to you now, when you understand how it works, you can now take it to your job, but with very secure guardrails because some jobs don't allow for it, some jobs allow for it irrespective.
Speaker C:You don't want to put your trade secrets in ChatGPT or any tool for that matter.
Speaker C:But then you want to look at how it can be useful for you at your job.
Speaker C:You want to read up on use cases if your company is supportive of AI, because some companies are not, pitch it.
Speaker C:If they're not supportive of it, then it might be time for you to learn on your own and find who supports your vision.
Speaker C:So that's my spirit.
Speaker B:I Love that.
Speaker B:I love the idea of finding something that you're passionate about and honestly just getting your hands dirty.
Speaker B:Right.
Speaker B:I think that'd be the best way to learn and to start to understand the technology is again as dynamic as agile is.
Speaker B:Like quickly growing is just to get experience with it and exposure.
Speaker B:So that's really helpful.
Speaker B:And then building on to what you said before, but the idea of like pitching it to your organization, I think it's such a valuable thing that you can do as an employee to be able to say okay, here's an opportunity, here's area of improvement that I see.
Speaker B:And then being able to say like there is a solution for it and to actually recommend that and whether or not it actually gets implemented the, the art of pitching your ideas and like that's a very useful skill.
Speaker B:So I'm sure our viewers going back.
Speaker C:To storytelling which is unique and most.
Speaker B:Important skill 100 I could completely.
Speaker B:So if you had a magic wand and solve one issue in the world with AI overnight, what would it be and why?
Speaker C:I think it's children education.
Speaker C:I like that it's children education because there's so much economic disparity or income disparity rather and some people don't have the opportunity to learn compared to others.
Speaker C:And with AI I feel that it can be used to reach children who are less privileged also including children who are privileged to be able to come up with very, very creative ideas.
Speaker C:With the old advent of the Internet, I feel that the world just went one way after it picked right.
Speaker C:So it's either you're a digital marketer or you're a programmer or you're this, anyone is creating a robot that can cook for me.
Speaker C:So I mean our children have less like they're very first spirited so they could come up with different ideas.
Speaker C:And I feel like we haven't tapped into the brain of children, children to come up with this groundbreaking ideas because as adults your, your behavior starts to form and you start to align based on, on the society or whatever you want it to be aligned with.
Speaker C:But as children they have so much free spirited ideas.
Speaker C:So that's, that's one thing also for children who are very disabled.
Speaker C:I remember like growing up I used to be like I had tonsillitis and there are times where I will not be able to speak, I won't be able to write, I will not be able to see.
Speaker C:I took out the tonsils though.
Speaker C:But I wish at that time, you know, I had something that could help me to, to learn or to help or Support me when I was, when I was sick.
Speaker C:So imagine children with like cerebral palsy, like people who are very, very disadvantaged when it comes to being able to use their limbs of their, of their hands and having that support for them.
Speaker C:I think that that will make the world a whole better place.
Speaker B:I completely agree.
Speaker B:And building on the idea of being able to reach children, to reach different type of children, I think that's one element of generative AI that's made it so popular is the fact that it can really tailor that messaging and create something personalized for you in a very quick, easy way.
Speaker B:And especially for children, and the fact that they have different learning styles or, you know, they engage with content, that ability to personalize, really create tailored messaging, I think that would be so impactful, especially for that demographic.
Speaker C:I agree, I agree.
Speaker C:So hopefully my magic plan comes to life.
Speaker B:Absolutely, absolutely.
Speaker B:So building on the idea of, you know, education.
Speaker B:So you, you're also an educator, which is fantastic.
Speaker B:So how do you bridge the gap between academic theory and real world AI applications for your students?
Speaker B:Like, how do you make it real for students?
Speaker C:So I took a break from teaching, from teaching at the school.
Speaker C:And I do more like professional trainings and all.
Speaker C:But I remember my last quarter which was not very welcomed by the students.
Speaker C:Not all of them, some of them welcomed it.
Speaker C:I went beyond the theories.
Speaker C:So, yes, we know AI should be used for X use case.
Speaker C:However, I want you to come up with the society you are, what is required, what the regulation says, and then tell me how you're going to approach this situation.
Speaker C:So I, I stopped marking results.
Speaker C:I started marking thought process and the ability to navigate through complexity, which if you go to a night like a normal school, they don't necessarily teach those things.
Speaker C:Um, so it was quite tough for the students to grasp.
Speaker C:But at the end of the day, coming out of the program, they're like, okay, now I understand what you're saying, because the workforce doesn't care about your theory.
Speaker C:Like, what can you do?
Speaker C:That's what you're, you're marked upon.
Speaker C:So I am actually seeing education changing and I hope North America can catch up to it, where they're not testing knowledge, but they're testing applications.
Speaker C:And they're testing applications not just for one scenario, but for different types of scenarios, because that way you can grow critical thinking in people's minds.
Speaker C:And I feel that this is where the school needs to get to.
Speaker C:And the other thing I do is, which is funny, I actually bring job descriptions to class.
Speaker C:I might look at this job Tell me.
Speaker C:I map the syllabus to the job description.
Speaker C:Tell me which.
Speaker C:So what I'm teaching them, they would.
Speaker C:I said, tell me what part of this can be solved by what we're teaching now.
Speaker C:And then you start to see people come up with different ideas, different use cases.
Speaker C:And I also learn from them myself.
Speaker C:So it's not more the theoretical way, it is now the application way and what you can do.
Speaker C:So that's how I approach it.
Speaker B:I think that's so brilliant because it's forcing them to make those connections.
Speaker B:And even for people, non technical people that are looking to get into that space, a lot of times I hear like, oh, I can never be in, you know, like AI or technology because I'm just not technical enough.
Speaker B:But because technology and by proxy AI is just so multifaceted.
Speaker B:There really is experience you can draw on in your previous experience that you can actually use for that role.
Speaker B:And one of the biggest, one, I want to say one big one thing that is helpful when starting to envision like can I actually be in this space?
Speaker B:Is to actually go through the process of making those connections.
Speaker B:Okay, you know, how does this relate to this and how can I use this to that?
Speaker B:So I think that approach not only helps the information like stick and stick better, but also helps that student envision that like, wow, this is real and I can see myself in this.
Speaker B:So I think that's so brilliant.
Speaker C:I agree.
Speaker C:And just something to say like a student might come from international diplomacy and law and another student might be a data scientist.
Speaker C:The way they approach a problem will be different.
Speaker C:We all know what the problem is.
Speaker C:So professors need to start looking at the diversity of thoughts and also educating themselves based on, on what this is.
Speaker B:Instead, just to your point 100, I vote for you to rewrite the curriculum, redesign it business goals.
Speaker C:Maybe.
Speaker C:I would love that.
Speaker B:That's fantastic.
Speaker B:So a lot of people also, when hearing about AI like they are, you know, excited for the possibilities or seeing organizations start to adopt it and start to try to capitalize on this opportunity.
Speaker B:But a lot of other people are also kind of concerned.
Speaker B:My gosh.
Speaker B:Well, I jobs like do, is there a future?
Speaker B:How do I navigate?
Speaker B:So what would be your advice to people that are concerned about maybe AI displacing some more traditional types of roles and how they can prepare for that.
Speaker C:So the third part is AI will replace some roles.
Speaker C:AI might replace my role in three years, who knows, right.
Speaker C:The way I approach it myself is to find the new areas that are growing.
Speaker C:So I read a Lot of job reports.
Speaker C:Like I told you, I just found one today.
Speaker C:I'm like, oof, let me read this.
Speaker C:That way I know what skills are going to be in demand and I can upskill myself when there's less pressure.
Speaker C:So I actually do this on it every six months because I don't want to be caught on guard, you know.
Speaker C:So I'll say people need to start with that.
Speaker C:And I know that as you grow older sometimes it's hard to learn.
Speaker C:And then, and I'm realizing that as I grow older it's so hard to like assimilate things, especially when you have responsibilities or your mom, your dad, you have all the kids and all.
Speaker C:And this is where you have to change your learning style to.
Speaker C:For me now I follow a lot of creators who are in the space.
Speaker C:I summarize articles for myself very fast and I look at what are the skills I have that people don't have and I can brand myself for the next role that is coming out.
Speaker C:And then I start to market myself.
Speaker C:So I actually create my own job descriptions myself.
Speaker C:Like I'm okay, what do I want to be, what interests me in the next six months or seven months and then I go after, I go by it or go after it.
Speaker C:And in five months if I'm bored, I find what is in the man in the market that also aligns with my skill set so that I could also pivot at the same time.
Speaker C:Now for people that are near retirement, it's a hard time.
Speaker C:Like I absolutely sympathize with them because they're about to get off.
Speaker C:But if you start with what your path like, what you're passionate about and what is fun for you, I feel like you can actually make money in this creative market without necessarily having to be very technical.
Speaker C:So it's just using AI to boost that part of you that you like, that you love and then using it to come up with creative ideas for yourself.
Speaker C:So again, it is here to stay.
Speaker C:Just like the Internet, people found jobs afterwards.
Speaker C:It's just how fast can you evolve yourself?
Speaker C:Which is the tough part.
Speaker C:And then you have to figure out what works for you from a personalized and go based on your lifestyle and what you want for your life.
Speaker C:So that's my advice to people.
Speaker B:That's such great advice.
Speaker B:And they say the only constant in life is change.
Speaker B:And what I loved is the ability to be proactive and to be forward looking and to understand what is in your control versus what isn't right.
Speaker B:Like you're never going to be able to change, to control how much things change, what changes AI might ring about, but we can control how we prepare ourselves for that wave is to do things like you said, like, you know, upskilling, finding what you're passionate about and seeing ways to keep learning and evolving as things change.
Speaker B:So that is fantastic.
Speaker B:So the very, very last question I'll ask you, this was such a great conversation, but I would love to know if you have the opportunity to restart your career, knowing what you do now, what would you do differently, if anything, and why?
Speaker C:What would I do differently?
Speaker C:You know, I asked myself that question.
Speaker B:I don't.
Speaker C:I don't know if I would do anything differently.
Speaker C:I think I would do more of.
Speaker C:Well, you're right.
Speaker C:I would do more of some things.
Speaker C:So I will do more of working for people that support me as well as working for people that are doing things that very valuable, that might not like me giving that my mental health is not affected.
Speaker C:A caveat.
Speaker C:And what that means is there's some people who do cool jobs and cool stuff, but they have terrible personalities.
Speaker C:It's being able to, for short period of time, dedicate myself from learning under them, to learn and then moving out of that role.
Speaker C:I think I would do.
Speaker C:I would do more of that.
Speaker C:But in all, I would say I've had a lot of people that have supported me and, like, I've been able to get here to tons of people's help.
Speaker C:Like, I can't even mention them because at every stage of my life, there have been people that have helped me that I've kept in touch with.
Speaker C:Some people, I haven't kept in touch with them because life has been very busy for them and for me, and they don't have time to sync with me.
Speaker C:So I would just say that everybody says, follow your passion.
Speaker C:You know, if it's too tough, get out.
Speaker C:If it's too easy, get out.
Speaker C:I would just define what is valuable to you at that moment and stick with it for period of time to learn, and that's it.
Speaker C:And just moving forward with your life.
Speaker C:And don't let people define what you should do or not do, because it's in demand.
Speaker C:Cover your own space.
Speaker C:That is in demand with the market and valuable to you based on your uniqueness.
Speaker C:So that's what I would do.
Speaker B:I absolutely love them.
Speaker B:That also speaks to owning your career.
Speaker B:That is so fantastic.
Speaker B:Well, Tavi, thank you so much for this discussion.
Speaker B:I personally learned so much, and I'm sure our viewers gained just as much insight as I did to our audience tuning in today.
Speaker B:Thank you so much for listening and for your support.
Speaker B:Stay tuned for more exciting interviews with amazing women like Temi who are trailblazers in the technology world.
Speaker B:You can listen to more episodes on Apple or Spotify podcasts and be sure to subscribe and follow our Instagram page itlove Podcast.
Speaker B:Feel free to drop a comment and let us know what you enjoyed most about our podcast, what topics you'd like to hear, or who you'd like us to interview next and share this podcast in your network.
Speaker B:Thank you so much and wishing all of you a wonderful day week months ahead.
Speaker A:So there you have it.
Speaker A:We trust that you enjoyed this episode and are looking forward to the next month.
Speaker A:Make sure to subscribe to our podcast so you never miss an episode.
Speaker A:Until then, thank you for listening.
Speaker A:With love.
