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Impact of Artificial Intelligence in the Development of Modern Cities
IMPACT OF ARTIFICIAL INTELLIGENCE IN THE DEVELOPMENT OF MODERN CITIES It has been two years since I was remove—ultimately, generating $2.9 trillion in business value designated as the project managby 2021”. Lisa Harper, PMP Adjunct Professor Morgan State University er for an artificial intelligence (AI) project. In the beginning, I was drinking from the fire hose because I knew nothing about AI. One of the first things I learned while working on the AI project is that the core concept regarding AI systems is that their predictions are only as good as their data. With this knowledge in mind, preparing and cleaning data is clearly something that I had many questions and read a has become a more vital part of the project process. With our lot of information because I knew that I had some catching project, during the proof of concept, the AI vendor reviewed up to do. My constant questions and clarifications caused the 97,400 contracts that equated to over one million pages. Imagsolution architect on the project to put his earphones on, roll ine that! Because the data was in structured and unstructured his eyes and grit his teeth many times in the last two years. This formats, this step was the most labor-intensive part of buildwas not due to his disinterest in helping but due to differences ing the AI system’s proof of concept. It took a while for data in our communication styles. His focus was on tasks and results analysts to complete this essential step with the help of the while my focus was on people and not too many details. professionals who do the job every day. Based upon the solution architect’s communication style, I learned that it is best not to ramble and to be clear, specific and to the point (Communication, miscommunication or the lack of communication has a significant impact on a project). To improve communication, my recommendation is to profile team members to create self-awareness (with the use tools such as Myers Briggs and DISC) and take time as a team to learn and understand other’s styles and make an effort to approach and engage your team members in a way they prefer.
I adapted by learning on the job, listening to webinars and attending conferences. Although it is not mandatory for project managers to be technical experts in the field of projects for which they are responsible, it is good to familiarize oneself with the basic requisite knowledge and information because these will help improve stakeholder engagement and management. With the rise of AI and other emerging technologies, it is becoming less of a “nice to have” and more of an essential concept for technical project managers to understand. In a recent press release from Gartner (Stamford, 2017), a world leading research company, they state, “by 2020, AI will generate 2.3 million jobs, exceeding the 1.8 million that it will Extra considerations were needed to manage the team and scope resulting in longer project estimates to build the right data infrastructure and to prepare data in disparate formats. This specific task was done in linear steps, which did not fit neatly into typical project methodologies such as Agile or Waterfall, although the proof of concept as a whole utilized sprints.
The project team quickly realized that humans needed to perform three crucial roles: 1. To train machines to perform certain tasks; 2. To explain the outcomes of those tasks, especially when the results were counterintuitive or controversial; and, 3. To sustain the responsible use of machines.
Machine-learning algorithms were taught how to perform the work that they were designed to do because the data was a combination of unstructured and structured data. The proof of concept proved that we were buying the same product from the same vendor at different prices. Previously, we did not have visibility into the data nor did we have visibility into what other divisions were purchasing. We were shocked by some of the results and we found price differences upward of 322% on the same product purchased. I ran into familiar and new challenges which highlighted the importance of using resources and asking questions to be aware of potential issues throughout the entire process. This included the creation of the project’s scope at the beginning through to completion. In collaboration with the project communications team, a stakeholder engagement plan and a communication plan were created to ensure engagement and communication to help stakeholders understand and feel more comfortable with the uses and complexities of utilizing AI as a tool. It was important to communicate often and at various stages of the project and during its implementation. We wanted to educate our stakeholders about AI and its capabilities and more importantly, we wanted our stakeholders to know that AI is an enabler that empowers them and their operations.
Now let us talk about the impact of AI in the development of modern cities. How can a similar AI proof of concept help the city of Baltimore? Let’s think about AI being similar to hiring or on-boarding a new employee who will work in the tax assessor’s office. This new employee will figuratively work sideby-side with almost every worker in the tax assessor’s office. Considering AI in this humanizing way is essential to its future success in the city of Baltimore. As an example of the use of AI, the tax assessor’s office receives a lot of emails from residents inquiring about issues related to their taxes. The emails deal with all sorts of subjects from claims to address changes. The emails come into a central queue and are forwarded and answered when an employee is available after finishing all of their other tasks. Because of the growing volume of emails, the leader of the team felt that it was important to automate the process. A key task would be, identify the primary topic of the email and forward to the appropriate department. Robotic process automation, a form of AI, can be used to send the email automatically and use machine learning to classify the emails so that they are forwarded to the correct department. Also, a substantial amount of data will be required to facilitate the machine learning process and to help employees analyze the data in the initial stages of setting up the new AI tool. The tax assessor employees can now use time freed up by AI functions to deliver value back to the organization in creative, new and different ways. It will be important for the city of Baltimore to realize they do not have to eat the proverbial elephant all in one sitting. They can simply start with small changes or key business goals and let success do the talking. Build a beacon of light for the future where the human and the machine work side by side for better outcomes and greater employee growth.
References:
Gartner press release (STAMFORD, Conn., December 13, 2017). Retrieved from https://www.gartner.com/en/newsroom/press-releases/2017-12-13-gartnersays-by-2020-artificial intelligence-will-create-more-jobs-than-it-eliminates
