Artificial Intelligence in Digital Asset Management

With the rise of the machines(!), we explore Artificial Intelligence, Machine Learning and how they stack up to humans.

In digital asset management, Artificial Intelligence continues to be a widely discussed topic at conferences, amongst experts, and in development meetings. If you work in Digital Asset Management (DAM), you may have heard of Artificial Intelligence (AI) and Machine Learning (ML). When properly implemented, the duo can dramatically make your processes more efficient. While this sounds exciting, it may also sound concerning, as these technologies could revolutionize workflows and render certain roles in your company obsolete. 

AI’s application in Digital Asset Management ranges from facial recognition to automatic tagging and metadata application. Machine Learning helps these time-consuming tasks be done on a scale that would vastly outperform human effort. With AI and ML both becoming more prevalent, what role can humans play in the future of DAM – if we play one at all? 

THE POTENTIAL OF ARTIFICIAL INTELLIGENCE

To understand Artificial Intelligence (AI) and Machine Learning, we must first define both terms. Here are some simple definitions:

  • Artificial Intelligence (AI): Computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
  • Machine Learning (ML): A subset of AI that studies computer algorithms that improve automatically through experience. 

AI performs many of the same tasks as humans but on a larger scale and at a faster speed. Machine Learning systems allow for significantly larger economies-of-scale than human production, as computers and scripts do not tire of mundane tasks. Tasks they may take a human DAM Manager days to do can be done in a fraction of the time by intelligent systems. 

Machine Learning utilizes intelligent systems to run a variety of statistical models to extract relevant information from large sets of data. ML makes projects possible that would cost too much time and money to accomplish if they were done manually. The most important aspect of these systems is their ability to grow increasingly more effective, yielding more positive results over time. As the programs get smarter with more use over time, their level of sophistication increases exponentially.

Artifical Intelligence vs Humans

THE CURRENT STATE OF AI 

Several significant DAM tasks currently utilize AI and its power . For example:

  • Using facial recognition to identify employees, sports players, and other figures that appear in photos or videos. 
  • Keywording and tagging assets based on the subject matter and material of a given asset. 
  • Reading PDFs and other documents to create tags related to the text they contain.
  • Analyzing sports gameplay assets for jersey numbers, which are then used to automatically identify a specific player. 

While the current applications of AI are powerful, they are far from perfect. ML systems take time to learn new sets of keywords and images in order to accurately identify them. Currently, these systems are not the most effective way to identify and apply large amounts of complex, custom metadata to assets. Human judgment is currently far superior to the technology that is widely available to most organizations. 

The human brain is always seeking to expand and make new connections, always improving, learning, and adapting. While AI can distinguish photos of cats from dogs with extreme efficiency and speed, it lacks the ability even a three-year-old human has to walk into a room and successfully navigate a complex set of obstacles without a clear set of instructions. While the future is bright for AI, it likely won’t replace humans working in DAM in the foreseeable future.

CONCLUSION: ARTIFICIAL INTELLIGENCE VS HUMANS

Artificial Intelligence can be an exceptionally powerful tool, with tremendous potential and significant implications for the future. However,  it is inferior to the human brain and cannot replace the need for human judgment in most DAM processes. In sum, the human brain is still the superior tool for effectively managing your digital assets

Interested in learning more about technology in the Digital Asset Management space? Contact our team of DAM experts today!

Danny Karbassiyoon

Danny Karbassiyoon

Danny leads growth at Stacks enjoys deploying efficient, effective process that is measurable. He is passionate about building rich experiences through customer and product development while working in small, ambitious teams eager to build things from the ground up.

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