Erin Davis: Welcome to REAL TIME, the podcast for and about REALTORS® brought to you by CREA, the Canadian Real Estate Association. I’m Erin Davis, and in this episode, we delve into the present and look to the future. Artificial intelligence, AI, isn’t new, right? But with the growing popularity of generative tools which seemingly develop endless streams of content, it’s all anyone can talk about, so how might AI positively or negatively impact your business as a REALTOR®? On this episode of REAL TIME, we’re going to ask those questions. We have the privilege of hearing from data and machine learning product leader, Sharon Tehrani of the CBC.
We look at the opportunities and risks of incorporating AI into your business, specifically as they relate to creating and distributing content and how to use AI responsibly and productively. Here we go. Welcome to REAL TIME, Sharon. AI is such a hot topic right now, but presumably overwhelming for a lot of people, so can we start with a quick 101 on a few things, like for example, what is artificial intelligence?
Sharon Tehrani: Absolutely, Erin. Artificial intelligence, which is commonly referred to as AI in a short form, aims to develop intelligent machines that can accomplish tasks typically require the human intelligence. The main object is to replicate human cognitive abilities, enabling machines to think, learn, and make decisions. There are two primary types of AI. One is called narrow or weak AI, and the other one is general or strong AI. The narrow AI operates within a certain boundaries, and it cannot be generalized beyond the specific domain that it’s being trained on.
As an example, the chatbots that answer the customer questions, the autonomous vehicles, order recommendation systems, they are considered as narrow AI. On the other hand, we have the general AI, which is focused on highly autonomous systems that literally possess the human intelligence. They can learn, understand, and apply the knowledge to different contexts and problems.
Erin: I think I’m following you, you’re a good teacher. Now, my next question is out of left field, but is ChatGPT the same as AI? Or is it a brand name like Kleenex is to tissues? What is ChatGPT?
Sharon: ChatGPT is a sub-branch of the AI technology. They are the predictive language models that using the deep learning architecture to learn from the statistical patterns and relationships within the language. When they are trained and they gain the knowledge, they can be used to generate responses for us. You use just the input prompt to put some requests, provide enough context for those. Then based on the data that the models trained on, they can provide you with impressive and coherent responses.
Erin: Now, before we get in a bit later about how this can affect and impact, and improve life for REALTORS®, what’s the difference among terms like artificial intelligence, machine learning, and machine intelligence?
Sharon: When it comes to this field of technology, there are so many terminologies. Let’s start with the artificial intelligence or AI. This is the broadest terms. It encompasses the entire field that try to create intelligent machines. The machines that can perform the tasks such reasoning, problem-solving, decision-making, understanding natural language, literally what we are doing right now, as humans. Then we can go to the machine learning, or in short form we call it ML, which is a subset of the broader field of AI. In this field, we are trying to come up with the algorithms and statistical models that can learn and improve from the data, and provide us with some predictions and decisions.
If I want to give you a practical example in machine learning, I can mention the housing price prediction, which is very relevant to their real estates and REALTORS® for sure. We can use the features about the house, for example, the number of the bedrooms, of where is the location is, in order to provide the optimal price for that house in the future. Finally, machine intelligence, which is a more comprehensive term that includes both artificial intelligence and machine learning. It is referring the machine’s ability to exhibit intelligence and perform the tasks that humans are doing these days.
Erin: Let’s focus on ChatGPT, if we can, for a moment. It’s of course just one of many AI language tools that have gained so much attention lately. It’s certainly the one that I see the most. Can you tell us how these predictive language models work, Sharon?
Sharon: Absolutely. Predictive language models, ChatGPT or GPT-3, which is the model behind the scenes. We have BERT, T5, these are all technical terms that’s being used in this area. They’re working based on deep learning architectures or transformer models. As I mentioned, the whole idea that we use vast amount of textual data that is available in the public to learn the statistical pattern and relationship in the language, and these models using the inputs that the user provide with them and the context, and the knowledge that they gain from the training data in order to provide those responses and original content for the end users of them.
Something that I would add with these technologies, that none of these models have a true understanding or consciousness about the responses that they are providing. It is the responsibility of the humans to provide enough supervision and critical evaluations to make sure the accuracy, relevance, and ethical use cases of these models when it’s come to the real-world applications, because the outcome of these models can negatively impact the users and the businesses.
Erin: I can only imagine that it’s not something that you can set and forget. It could send out an email, for example, that might not have the human touch, so it still does require that supervision and evaluation. Humans aren’t out to the picture by any means here.
Sharon: Absolutely. All of those outcomes from these generative models needs to be evaluated by the human. You need to do the fact-check if the information that being produced by these models are correct or not. I never suggested blindly just copy-pasting what’s being created by these generative models. We need that creativity of the human to make sure that we build that deeper level connection with the audience of our content. It’s only can happen through the creativity that human brings to content creation.
Erin: Next up on REAL TIME, more on ChatGPT and how it’s being used, plus the opportunities, the what’s in it for you and your business. Real intelligence means you never stop learning. CREA’s learning hub covers all things Canadian real estate, newly re-upped to be more interactive, user-friendly, and super easy to navigate. That’s the learning hub. Now, back to Sharon Tehrani, who’s on the top 10 list of women in AI in Canada, on REAL TIME. How are businesses using this technology, Sharon?
Sharon: If I want to focus more on the predictive language models, the businesses start to leverage them in order to enhance their operations and deliver the value to their customers. Some of the practical examples is customer supports, which can be provided through chatbots and virtual assistance. You can handle the customer inquiries, provide the information to them, and assist them with common support request. Because these models are capable of understanding the natural language, so they can generate human-like responses, which leads to improving your customer service and the response time.
Another main application of them is content generation. These models are capable of creating articles, blog posts, product descriptions, social media posts, so you can leverage them in order to automate your content creations mainly when it comes to the large volume of tasks that you have. Another area can be language translation. If you are a business which requires multilingual support, you can leverage these models in order to just input a text in one language, and these models can create and generate translation in other languages for you.
The final piece, we know that all of the businesses try to move towards data-driven decision-making, so you need the analysis and reporting to make more informed decision. These models are capable of analyzing the unstructured data such as your document, your textual reports, and they can extract the valuable information for you, and then you can use those insights in order to make the decision for the next steps in your business. By this way, you are saving time and efforts that you are right now putting into the manual analysis.
Erin: What are the biggest opportunities, Sharon, for the future of how we work? What do you see are the really bright lights here for AI?
Sharon: The opportunities that I can see by leveraging the AI tools are, I would say, endless, but they can be used to foster efficiency, personalization, and innovation in work processes. If I want to provide some examples when it comes to the employees, it can help with collaboration and teamwork by providing the ideas, helping in problem solving so the teams can work together more effectively when it comes to collaborative tasks. It can help with personal productivity and organization of each individual person as well, because they can serve as a tool for assisting you with your task management.
Setting the reminders, providing you with the recommendations, and how to prioritize your tasks, so you, at the end, of the day optimize your workflow and it’s going to lead to increase the productivity. Another part when it comes to a more user end, we can have intelligence customer service. You can leverage these technologies to resolve the common issues, providing support in a conversational manners for your end users, and tailor the conversation based on their needs, and provide with more relevant and personalized experience for them.
Erin: Do customers generally know that they’re conversing with a virtual assistant? Like, do you make that transparent and say, “Hi, I’m your–” You wouldn’t say chatbot, but we see this on websites and that sort of thing, Sharon. Is it something that you put out there and say, “Hello, I’m Steve’s virtual assistant, and here are some listings that would be great for you”? Or do you just do it on the down low and put out the responses there? Because I know REALTORS® like so many of us, there aren’t enough hours in the day when there’s so much you want to accomplish. What is your experience in this in terms of communicating as a virtual assistant?
Sharon: From my perspective, the best approach is to be transparent with your customers and end users, mainly when you are leveraging any AI applications into your businesses. When it comes to the chatbots, the best approach to let them know ahead of time that they are talking to a virtual assistant and a chatbot, and not the human behind the scenes. That transparency helps you to build the trust and more authentic relationship with the customers that you’re serving. When it comes to the chatbots and have them as part of your business, first of all, you should see what kind of chatbots that you are looking for.
Do you just looking for some typical answers or question, or are you looking for a more conversational base? Because based on the application that you are looking for, the implementation, the cost, time, energy in order to incorporate that is going to be different. Again, I will add that transparency with the customers is a key in incorporating the chatbots into your business.
Erin: You’ve worked so hard to build these relationships, human to human, that it is important to remind people that there is still a human behind it, you’re just getting a little help, if I understand correctly.
Sharon: Exactly. For example, if there are so much typical questions that the customers have, so you can use chatbots in order to address them in a stuff like having a human behind the scenes to answer those questions. At the same time, you can provide this support 24/7 meaning that whenever the end users feels that they have a question, so they can reach out to the chatbot and get the information that they are looking for. In this way you can increase the productivity and your employees or the REALTORS® in this specific case can focus on more high-valuable task in the workplace rather than just doing these repetitive assignments and questions.
Erin: Let’s drill a little deeper in now on generative AI now that we know where we’re going, what we’re talking about. Sharon, tell us how is AI transforming the way businesses can create and publish content? You touched on that and that it can be such a beast to keep putting out relevant information all the time and coming up with new ideas, and that sort of thing. Tell us how it’s transforming the business.
Sharon: Very good question. When it comes to the generating content, AI made a significant advancement in this fields. Now we can see that these tools can be leveraged into the business, mainly a productive tool for content creators to help them with brainstorming ideas, generating the drafts, providing real time feedback and suggestion. It can be a huge assistant in copywriting, editing, proofreading, and even enhancing the efficiency and quality of the content that’s being created. From my POV, it is very unlikely that it’s going to be fully replaced by the human.
The reason being because when it comes to the content creation, the human inputs, creativity, judgment, emotion, empathy and cultural context, they are not something that AI systems at the current state can fully replicate. In order to create a content that on a deeper level resonate with the audience, we still requires that human piece in content creation streamline. I will see the generative AI just as a productive tool and collaborative tool for the content creations. That being said, this fold is evolving on daily basis. We may see some changes in the future, but I don’t think so something is going to happen or fully replace in the near future.
Erin: Is there an opportunity to use AI to make your content even more relevant or, in an oxymoron kind of way, more personal?
Sharon: Absolutely. When it comes to using AI in order to make content more relevant and personalized, there are huge opportunities there. The first one coming with content recommendation. These AI algorithms have the capability to analyze user data, what they prefer to consume, how they are consuming the content. Based on this information, they can understand the individual interest and start to suggest relevant articles, videos, products, and services to them. The other one, even they are capable to customize how the content is presented to the audience.
What is the layout should be, what is the design based on the user preferences. Other things that can be leveraged is, we can do sentiment analysis, analyzing the feedback and comments of the audiences on the social media posts and interactions, and then based on their opinions and sentiments, we can incorporate those insights to provide them more relevant content in the future, adjusting our marketing messages, and see which areas we can improve with the audiences.
Erin: When it comes to REALTORS® though, and I don’t think we can stress this enough, and you’ve certainly touched on it, again, this is a tool that would be complementary. It would go with and not replace the personal relationship with your client, because if I understand correctly, other than catching on to certain words and responses, it has no sense of empathy or understanding human interactions. Right?
Sharon: That’s absolutely correct. It’s just going to act as a complementary role when it comes to the real estate. That authentic relationship that you have with the clients is going to be essential. This is not something that can be replaced by artificial intelligence. It can just leverage to add values to your business. For example, you can enhance your efficiency, you can provide more personalized insight and recommendations and improve your customer experience by leveraging the chatbots into your business. At the end of the day, that human interaction, that empathy, the insight that you are gaining from your face-to-face interaction needs to be prioritized even when you’re using the AI technologies as a REALTOR®.
Erin: Back to Sharon Tehrani in a moment as she lays out some of the risks that come with using AI. Loving REAL TIME? So are we? In fact, we have 40 episodes for you to delve into. Hear from experts from world-renowned architects to TV designers, marketing geniuses, and of course leaders from your Canadian Real Estate Association. It’s all just waiting for you at REAL TIME, the podcast for and about Canadian REALTORS®, from CREA.
Now we’re back to our conversation with data and machine learning product developer for the CBC, Sharon Tehrani, on REAL TIME. Let’s fly into the danger zone here. What are some of the top risks or considerations, Sharon, around using AI? You’ve been doing this a number of years, probably from the jump. How can businesses use AI, specifically generative AI responsibly?
Sharon: When it comes to applying AI, again, including degenerative AI that we were talking about it a lot in this conversation, it comes with lots of risk and considerations. I’m going to name few of them, but the list can be endless sometimes. The first one I would talk is bias and fairness. All of the artificial intelligence systems highly depends on the data in order to provide us with the outcome. If the data is biased, then it can provide some discriminatory outcomes which can impact the business and the end users of our products.
In order to minimize that and make sure we have enough fairness into our data, we need to make sure that we using the subject matter expert to de-bias the data as much as possible and make sure we have a diverse and representative data. Another factor I would say, we need to use our human judgment as well to make sure that these datas are unbiased as possible. That being said, at the end of the day, there is going to be a certain level of bias in all the models and the data because we are humans. We have some biases, and we are going to incorporate them when we are working with these new technologies.
The other point is lack of transparency. The artificial intelligence model are very complex. We call them that they’re operating as a black box. Literally, we don’t know what’s happening inside them, and it’s very difficult to say how they are reaching to certain decisions. This lack of transparency can impact the trust of you and the stakeholders or end users of the AI products. We need to work and provide more explanation of what’s happening behind the scenes for the end user to build that trust with the stakeholders and end users of these AI systems.
Another huge area is data privacy and security. When it comes to the data collections, we know that there’s lots of data including sensitive information, so we need to prioritize data privacy making sure we have enough measures to protect the user’s data and company data from breaches and unauthorized access. For example, not everyone in the company requires access to all the data, so we can create the levels to make sure only certain people access to the information when it is needed. Again, if someone like hackers access to the data, they may use it unethically and it can have so much negative outcome and impacts on both business and the users.
The final point I will add, again, this list can be endless, is the ethical considerations. For example, they’re talking about surveillance, autonomous weapons, or even manipulating the public opinion. As businesses and as people who wants to leverage AI, we want to make sure to establish ethical guidelines and frameworks to ensure AI is used for valuable purposes, and it is aligns with our business values and our social norms. These are the points that I will edit. I can continue talking in this, but I know we want to go over other topics as well here.
Erin: It does sound like a lot, and it’s all valuable, but tell me, Sharon, how can those inputting the data make sure that it’s staying in line with the values of your company? Because if you’re hired to come into a company and this company has been here for 20, 30 years, how are you expected to just step in and know that, oh, this company, this REALTOR® stands for this? How do you get that?
Sharon: When you join to a new company as a new employee, and you are a newbie and a newcomer, first of all, you need to learn about the business, learn about the values that this business is functioning on. Then when you learn, as I imagine you’re a technical person, you are a data scientist, when you learn about all of those business values, and now you’re trying to incorporate the AI in solving the business problem, in every stage of your decision-making, you need to consider those values. When it comes to selecting the data that you want to use for training the model, when it comes to decision-making, when it comes to the outcome of your model.
You have to consider the business value from end-to-end. Again, I do suggest that always talking with the people who are working in that organization for a while, talking even with the leaders, what they are looking for. Because at the end of the day, the outcome of these models that you are putting out there, you are responsible and accountable for them. You have to make sure that they are aligned with what you’re looking for and what your business is looking for and wants to achieve. We need to, again, educate ourselves around the business value ahead of time and make sure they are applying into our end-to-end decision-making when it comes to leveraging any AI systems.
Erin: When we return to our discussion of AI with Sharon Tehrani, tips to get started with artificial intelligence, around 250,000, that’s how many listings you and potential clients find simply by clicking on REALTOR.ca. There’s so much more than properties. They’ll find design trends for the future, how to narrow down needs and wants for the place of your dreams, all at your and your client’s fingertips.
REALTOR.ca, no wonder it’s the most popular and trusted real estate website in Canada. Now, to dollars and financial cents. When it comes to implementing AI in your day to day, here again, Sharon Tehrani, data and machine learning product developer for the CBC and expert on artificial intelligence on REAL TIME. Is it best to start with free tools? Would that be the dipping your toes into AI step that you would recommend, Sharon?
Sharon: My answer would be yes, because when you comes to applying the AI systems into your business, the best practice is to start small with some small projects and prototypes and see how it’s going to help your business in order to solve the problems that you are facing right now. Validate the concept before you want to commit to something bigger. When you start small, it provides you with this opportunity to iterate later.
To learn from this POC that you built, to observe the potential risks that we mentioned about the data privacy and the things that can go wrong. Then when you validate all of those aspects and see what are the potential risks, then you can think about, now maybe this is something that my business can value from. Then you can start thinking about committing to a more enterprise plan that, again, provides some benefits that the free tools may not be able to give you.
Erin: You miss out on the free AI downtime. That’s a thing to consider as well, yes?
Sharon: Exactly. When your businesses heavily rely on AI system, you literally leverage that to solve your problem, so it’s very hard to afford extended periods of downtime. The free tools doesn’t have enough support and maintenance in place to address them. That is one of the main criteria you may want to consider invest more money and time, and go with those enterprise tools out there because they can provide you with the assistance and support, and technical troubleshooting that you require when you’re leveraging AI. Again, when it comes to the performance, they are better and more reliable, for sure.
Because the free tools doesn’t have the processing capabilities as compared to the enterprise one. Again, there are so many other benefits such as data privacy and security. You can customize the tools more relevant to your business. They are more sustainable when it comes to the long-term using them. Again, there’s so much features that comes with the enterprise tools compared to the free tools. That being said, the free tools are going to be the amazing starting point to gain some insights before you want to commit to something bigger.
Erin: I am so glad you mentioned money there, Sharon, because it’s burning a hole, not in my pocket, but in my head here. What are we looking at for a financial outlay? Are we talking tens and tens of thousands of dollars or– I don’t even know. How much does it cost? Can you ballpark us?
Sharon: That’s a very good question. I don’t have any specific number on top of my head, but it really goes back to the problem that you have and what solution you’re looking for. Yes, sometimes it can be costly, but one thing that I can comment on is that you can always invest on your employees to start building and incorporating those AI system into your business. That’s actually what I’m doing within my team.
We are building everything from the data pipelines to the end product that we are providing for the content creators. If you invest in your employees, that’s, I would say, the money that you need to spend in order to leverage these systems for your own business. I would say that’s going to pay off at the end of the day, mainly when you do that internal investment, because they can bring that creativity and innovation that comes with the AI in order to come up even with the other new ideas and think out of the box to help your business to stay ahead of game in these competitive markets.
Erin: It does seem like AI is here to stay. There’s no question about that, and it’s only getting more advanced. As you said, it’s changing day by day. How do you foresee it changing the workforce?
Sharon: AI is here and for sure it’s going to stay. It makes so much significant impact even so far. There are some key areas that I can mention about how it’s going to change the workforce. The first one is automation of repetitive tasks, so we can use this technology to just automate the routing tasks, and then the workforce can focus more on complex and creative aspects of their jobs, and this will lead into efficiency and productivity because we are freeing up the times of the humans so they can focus on more high-value activities. The other one is it’s going to lead to creation of new jobs.
When you leverage those AI technology, you need new jobs and functionalities. The people who will be able to develop, maintain, and oversee these AI systems. Their roles can be AI specialists, data scientists, AI trainers, and so many more. It’s going to transfer the existing job roles as well. Right now, we are having these traditional roles. When you bring the AI, it’s going to transform the current job titles and the employees need to start learning new skill sets.
Then they are able to work alongside the AI systems and relevance to their jobs and adding value based on the roles that they have within the organization. The final one I will add is it is going to augment human capabilities, so it can help with decision-making, problem-solving, and information processing. At the end of the day, it will improve the accuracy and efficiency when it comes to tasks, and we can see better outcomes both for the businesses and the employees as well because they can put their focus on more high valuable activities in the workforce.
Erin: In a moment, seamlessly incorporating AI in your business. Catch past episodes of REAL TIME where we talk intelligent design and green planning, marketing and promotion, home design ideas, and everything you need to help you be the best. Be sure to subscribe so you don’t miss our monthly episodes and download wherever you get the best podcasts. Now back to Sharon Tehrani who’s listed among the top 10 women in AI in Canada. She’s with us on REAL TIME. How will businesses need to pivot in terms of leaders and teams focusing on developing to effectively work alongside AI? What skills should they be focusing on?
Sharon: A very good question. The first one I will add is AI and data literacy. In order to be an effective leader and making informed decisions, or being an employee that can work alongside with the AI, you need to gain an understanding about the foundational artificial intelligence concept, the terminology, the potential applications. You need to learn about the data types, how they are collected, what is the quality of them, knowing how to do some specific analysis around the data. Then based on that, you are going to become a better leader when it comes to informed decision-making of how to incorporate AI.
Again, as an employee, you can work alongside with AI and bring the high value in your role. Another area and skills that needs to be worked on is creativity and innovation. The leaders should foster a culture of creativity and problem-solving, and ideation, because when you combining the AI, AI is mainly focused on thinking out of the box. If you combine the AI capabilities with creative thinkings, that’s where you can gain the most value out of these new technologies and stay ahead in the market. Everyone on the business needs to be educated on the ethical and social awareness, because this is one of the main challenges with applying AI.
Developing the skills when it comes to ethical decision-making, privacy protection, bias identification, mitigation, and ensuring that the outcome of AI system are fair and accountable, these are the essential skills that needs to be learned. Finally, it goes to continuous learning. I don’t know how many businesses, but if you consider the agile mindset, we know that the AI field is dynamic. It’s changing every day. The leaders and their teams should embrace this adaptive mindset. They need to have this culture of continuous learning. They can attend the conferences, the training programs, and making sure they know the latest changes in the market and they can leverage those technology into their businesses.
Erin: Lastly, Sharon, how can businesses make smart decisions around implementing AI? How do you determine the best use cases while still protecting your personal and company data?
Sharon: Very, very great question. The first step is to identify the relevant use cases. Not all the business problem requires the AI in order to solve them. When you find your use cases that AI can help to solve it, then you can start to build your AI implementation strategies, which is going to be aligned with your objectives that you want to gain as your industry. Now you identify your business objective, the next step to prioritize the transparency and accountability. As I mentioned, you need to make sure you are transparent with all the stakeholders because at the end of the day, you are accountable for the outcomes of these AI-driven decisions.
Always start small… begin with a very small-scale AI project. Validate your concept, learn from implementation process. See what is the impact on data privacy and security. This attractive approach is going to help you to come up with the better implementation of your AI strategy and minimize the potential risk that you may find along this journey of implementing AI. Make sure you’re implementing data protection measuring place like encryption, access control. You need to have regular security audits because again, privacy practices are very important when it comes to leveraging any AI into your business.
Make sure that you are continuously monitoring and evaluating the models. These models, again, can have sometimes unintended outcomes, which may negatively impact your users and business, so you have to monitor their performance all the time to make sure that their decisions are relevant to your problem. Finally, which is, I personally experienced it as well, involve the stakeholders, early stages. Try to make sure that they are part of your process. The stakeholders can be your employees, your customers, or partners.
Make sure they are part of the conversation when you want to implement the AI in your business and solve a problem, because you can value from their expertise, again, based on the roles and functions that they have in the organization. It will help with the transparency and building trust with them, and addressing the concerns early stages rather than being at the final stage and then try to get the bind from them. I personally experienced that, and I would highly recommend to have those conversations and involvement in early stage of your AI implementation.
Erin: Finally, how do you think REALTORS® can use AI today?
Sharon: REALTORS®. The first one is the customer service. We mentioned about the chatbots and virtual assistant in our conversation today. When it comes to real estate, you can have these customer service improvements and response time, and ensuring that your clients receiving the timely assistance in a very human interaction because they are capable of providing very human-like responses to the clients.
The other one I would add is the power of natural language processing and sentiment analysis. You can leverage these AI technologies to do the sentiment analysis on your customers, the social media posts, and gain an insight what the client’s preferences are and what is the market perceptions are, and then you can tailor your services and marketing strategies based on those insights.
Erin: Do you have any website or any place that you recommend people go to to get more information or to take another step into these deep waters? What do you think?
Sharon: When it comes to learning, I personally suggest the LinkedIn Learning.
Erin: You said LinkedIn Learning?
Sharon: Yes. It provides lots of high-level courses in order to gain an overall understanding about the AI, machine learning, and what’s happening in the market. I highly recommend that as a learning tool for anyone who wants to expand their knowledge and try to see the applications of the AI for their own businesses. Don’t afraid of the AI. It is just a new technology. To be honest, it’s not that new, it’s been here for a while. It’s just now it’s publicly available to the end users. Now it triggers a conversation in the public, but it’s been here for a while.
I do suggest just embrace the AI, start to work on your literacy around both the data and the AI, and see how you can gain the most value out of it. As I mentioned before, this is the responsibility of each individuals that use this technology for valuable use cases, use it in a ethical way. Being transparent about how they are leveraging it into their businesses. For sure, do not afraid of it. The goal is to make the life of human easier, not more difficult. I know it comes with risks and problems as well, but we can work on it together and solve it to make sure everyone can benefit from it.
Erin: Thank you. What a great optimistic note to end on, and we so appreciate your insight and wisdom today, Sharon. We’re very grateful.
Sharon: No worries. Thank you, Erin. Thank you for having me. It’s awesome.
Erin: REAL TIME is the podcast for and about REALTORS® brought to you by CREA, the Canadian Real Estate Association, production by Alphabet Creative, with technical engineering by Rob Whitehead of Real Family Productions. I’m your host, Erin Davis. Thank you so much for joining us, and we’ll talk to you again soon on REAL TIME.