Shaping the Future: Top Trends in Data Science, Machine Learning, and Artificial IntelligenceDecember 6, 2023
The future of data science, machine learning (ML), and artificial intelligence (AI) is being shaped by new and emerging trends within the technology landscape. These trends are defined not only by the demands of the rapidly evolving industries such as cybersecurity and healthcare that benefit most from them, but the interests of the community as well. The popularity of user-friendly software like ChatGPT and Generative AI has made a notable impact within the artistic community, as well as those generally interested in creating computerized imagery and writing. The emergence of this new and improved technology also has the potential to change employment as we know it in both positive and negative ways, by optimizing some autonomous tasks while monopolizing human-based jobs.
But how will data science, ML, and AI really affect our futures? These top trends in the field can give us some insight into where things are headed:
Automated Machine Learning
Automated Machine Learning (AutoML) is a useful process for data scientists, researchers, and analysts seeking to automate time-consuming, data entry-type tasks. This is especially helpful within the biomedical research platform, where the input of sensitive data is crucial for creating reliable models, yet tedious and prone to human error. Users are now able to use a raw data set to build a high scale, accurate, and iterative model based on algorithms and parametric rules. This automation of tasks, however, could be a cause for concern if it replaces the need for a human component entirely.
AI and ML have been integral to the field of cybersecurity for years but are just now receiving more public acknowledgement. Since AI and ML hacking tools are becoming more widely accessible to all users, malicious actors have a big advantage. Open-sourced applications like ChatGPT often make it easier to create more believable phishing emails or develop software that can compromise data and install viruses. But where AI and ML can help criminals, it can also help cybersecurity professionals in thwarting these attacks. Thus, advancements in cybersecurity training with AI and ML in mind are critical to helping prevent criminal behavior online.
New trends in analytics are providing more user-friendly solutions to those who manage big data and require better data visualization. Augmented analytics offers tools and applications for users to explore, such as suggestions, insights, or recommendations to help inform the user based on previous AI and ML collected data. These personalized features empower users by allowing them to get more value from their data through enhanced visualization, and many businesses are integrating augmented analytics into their evolving practices. This is especially useful for quantum computing, which can propel the creation of more intuitive generative software in the future.
Edge AI, also referred to as Edge Intelligence or Edge Computing, describes data collection and processing that occurs near the “edge” or close to a data collection site, rather than at an external server facility or via cloud storage. This proximity positively affects the speed at which processing can be completed and provides real-time feedback without delay. It also improves usages of power, bandwidth, privacy, and latency for better overall performance. Since it does not require an internet connection to use Edge AI, it can provide a higher level of security for sensitive data that could be intercepted online, which could be a critical and appealing element for many industries.
Responsible AI and Democratized Access
Responsible and democratized AI access calls for a more ethical approach to the use of AI and ML. This trend suggests that open access for all users is better than implementing a cost for access. It is argued that, by providing free access to this technology, this would actually improve employment opportunities by keeping the user in control, boosting overall efficiency, and prioritizing quality over quantity when it comes to production. By being an educated user with up-to-date skills in the newest technology trends, employees can ensure job security rather than AI replacement. However, open access can also pose possible issues like copyright infringement, loss of data, and misuse, which is why establishing a strong education in this technology is critical to preserving one’s employability and the integrity of the field.
Education in Data Science, Machine Learning, and Artificial Intelligence
Capitol Technology University offers programs in all areas of technology, including AI, Computer and Data Science, Cybersecurity, Cyber Analytics, and Management of Technology. The evolving trends of these fields indicate a sustained need for trained professionals to fill roles in these areas, leading the charge for advancement of new and improved technologies.
Visit our website to learn more about our programs and how you can secure your future career in these fields.