Looking Into the Future: AI, Streaming Databases, and the User
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New applications and possibilities of Artificial Intelligence (AI) are changing the way people interact with media and services. Examining how AI can work with streaming databases for potential application and end user experiences can be mostly conjecture at this early stage of AI application, but it is well worth exploring the possibilities. If we look at how AI is starting to be integrated into consumer streaming services, the potential for academic application, specifically streaming databases shows a possibility for what the user could be working with sooner rather than later (Hope, 2023).
At the moment, academic databases are in the process of harnessing AI to enhance the user experience and open up their deep web content to Large Language Models. This will essentially transform how the end user retrieves, interacts, and synthesizes research. According to respective database provider blog updates, EBSCOHost and ProQuest are both working to incorporate AI into most aspects of their interfaces (Holmes, 2023), (ProQuest, 2024) This improves on the past which was based on what is termed as relevant, as related to word count and occurrence frequency of indexed keywords, dictated in returned results.
Taking into account the article databases that will be utilizing AI for their users, it is highly likely that streaming databases would also use AI as a tool for bringing all aspects of a film to be thoroughly searched. Consider that in the future, that film footage is fed into AI and based on sound, dialogue and cinematography, these aspects could be filtered through with connections made to answer questions and provide informed summaries comparing multiple films. Imagine a database with ChatGPT, Claude 3 or Microsoft’s Copilot enhancing results! Video indexing that is driven by AI would potentially foresee a user’s requirements and make complex suggestions for video content (Kahn, 2022). Even examining roles of an actor/director/editor and how they have changed over the course of his or her career creates possibilities that modern computer processors would have no trouble in generating within a matter of seconds. “An advanced AI engine can analyze the intrinsic emotional profile of each content asset to create nuanced categories. For example, moods can be categorized as “tense, fast-paced horror” or “light-hearted escapism”. (Bergstrom, 2021)
“AI is not just curating content; it is optimizing it.”
Let’s look at four distinct areas that stand out when looking at the application of AI and its use for streaming databases. These areas are content optimization, enhanced search/discovery, predictive analytics, and improved accessibility. Below are the modified and added to results when the AI Large Language Model (LLM), Perplexity.ai, was asked about the future of streaming video and AI incorporation.
For content optimization, this will entail what drives more clicks in the interface. As for the marketing of content, visual data may change and adapt based on how a user interacts with content.
Enhanced searching and discovery with AI enhancements will make navigating large content libraries easier for users with more effective searches and more accurate connections made between content. Natural language processing will enable searches to be more conversational and offer multiple suggestions or paths to pursue.
Predictive analytics and AI will redefine the user experience with accurate suggestions that are more personalized than ever before. Although already in use to some degree, AI will exponentially improve the user experience in a predictive manner that is tailored and not generalized to groups of users.
Accessibility Features consisting of closed captioning and foreign languages will be easily retrieved when needed. “Features like automated closed captioning and language translation are becoming more accurate, thanks to AI, opening content to a broader, more diverse audience (Kahn, 2024).
“AI is not just curating content; it is optimizing it” (Sahota, 2024). Paid consumer streaming services are also on the verge of rolling out more AI features. Curated lists are already a common feature, but add in newer, more complex versions of AI, and the experience becomes far more personal to the end user. More than just metadata attached to a film, imagine AI peering into the entire script of a movie, analyzing cinematic styles and making connections to other films more accurately and quicker than the human brain can. The satisfaction from the experience would be pretty straight forward - the armchair cinephile becomes better informed and possibly more engaged with these connections that the human mind never suspected. New ideas start to come to light, which will encourage new research in film studies and beyond. The future will probably see even more complex applications for AI in tackling research queries, especially with the exponential growth of AI quality and complexity.
One drawback may be where databases and streaming services own the rights to a film and therefore cannot be fully indexed or analyzed. A future streaming database may have to resort to listing titles and a synopsis, but lack the content to fully utilize the full extent of what AI could do. This is what researchers already encounter in article databases where abstracts are present but lack full text content. Another issue occurs when films have not been digitized. Along with their lack of digital accessibility, many older films have obscured or nebulous rights that hinder streaming access. Perhaps AI can be harnessed to help deal with these hindrances?
Academic implications for the future of AI and streaming databases are evolving. This is now the task at hand for this early stage of incorporating deep web content such as research articles and film to utilize natural language to search and give the user a better interface. Speculating about natural language searching is just one area involving AI. In the next five to ten years, searching in databases will be very different than it is now. Gone will be the clunky feel of throwing out a fishing line and seeing what comes up. More detailed and specific results will enhance retrieval and the user’s experience. It’s an exciting time to see what comes next.
Works Cited
Bergström, M. (2021, January 22). AI is powering better recommendations on streaming services. Technology Magazine. https://technologymagazine.com/ai-and-machine-learning/ai-powering-better-recommendations-streaming-services
Holmes, J. (2023, September 21). EBSCO Information Services Pursues Generative Arti cial Intelligence (AI) Opportunities. News | EBSCO. April 10, 2024, https://www.ebsco.com/news-center/press-releases/ebsco-information-services-pursues-generative-artificial-intelligence-ai
Hope, D. (2023, December 12). AI creates global shift from cable to online streaming. SmartData Collective. https://www.smartdatacollective.com/ai-creates-global-shift-from-cable-to-online-streaming/
Kahn, M. (2022, February 11). The use of artificial intelligence in streaming services. TMC Net. https://news.tmcnet.com/topics/articles/2022/02/11/451487-use-artificial-intelligence-streaming-services.htm
Clarivate. (2024, February 29). In collaboration with its community of educators, ProQuest marks a milestone in trusted academic research. ProQuest®, part of ClarivateTM, launches AI-powered research assistant. April 15, 2024, https://about.proquest.com/en/blog/2024/proquest-part-of-clarivate-launches-ai-powered-research-assistant/
Sahota, N. (2024, March 20). Streaming into the future: How ai is reshaping entertainment. Forbes. https://www.forbes.com/sites/neilsahota/2024/03/18/streaming-into-the-future-how-ai-is-reshaping-entertainment/?sh=8aaf98e3056e
