Question

Imagine and choose one particular application of Data Analytics – Artificial Intelligence such as natural language processing, text to speech conversation, facial recognition, forecasting, medical diagnoses, self-driving cars, smart homes, smart cities, etc. Briefly describe how that chosen context requires the Data Analytics or Artificial Intelligence systems or tools. Give examples of how the chosen application can be actually implemented, such as using natural language processing to compose music, write essays or understand people’s emotions from social media conversations, etc. Potential benefits of applying data analytics / artificial intelligence into that chosen context? How to optimize the potential benefits or take advantages of potential opportunities from that context? Risks or ethical concerns about possible harms from applying data analytics / artificial intelligence into that chosen context? How to limit, minimize or mitigate the risks or unwanted effects from applying data analytics / artificial intelligence to that context? How can this data analytics / artificial intelligence application be related to other aspects of technology development in current and future trends?

Answer 1

Data Analytics/AI is critical in self-driving cars, where it processes sensory data to navigate safely. The application offers benefits like accident reduction and more independence but also poses ethical concerns and job security risks. Mitigation includes clear AI governance and workforce adaptation.

Step-by-step explanation:

To illustrate the application of Data Analytics or Artificial Intelligence (AI), consider self-driving cars. This field demands the integration of several AI components such as machine learning, computer vision, and sensor fusion to interpret and navigate the vehicle's environment. For example, AI algorithms can analyze data from cameras and sensors to detect obstacles, predict the actions of pedestrians, and make real-time driving decisions.

Moreover, self-driving cars present numerous benefits, including reducing accidents caused by human error, easing traffic congestion, and allowing individuals with mobility issues to travel independently. To maximize these benefits, constant refinement of algorithms, validation of AI decisions, and extensive real-world testing are essential.

Ethical concerns and risks include the potential job displacement of drivers, cybersecurity threats, and legal accountability for accidents. These can be mitigated through transparent AI governance, collaborative development of ethical frameworks, and progressive upskilling of the workforce.