Adaptive AI Systems: One of the Top Trends of 2023

Artificial intelligence has bloomed into existence during this decade. It has boosted productivity, efficiency, and growth. Without artificial intelligence we couldn’t have Face IDs, fraud detection, or even travel navigation. With that being said, as companies take more time to research this newly developing technology they have made extensive progress in adaptive AI systems. Research shows that data seems to be moving in favor of Adaptive AI Systems. Keep reading to find out why.

What are Adaptive AI Systems?

The problem with traditional AI is the inability to learn from the data it receives. As the name suggests, Adaptive AI systems are adapting to new information. It takes in data continuously and uses that data continuously. It adapts to changing environments and shifts with market behavior. This cycle helps the framework be constantly updated, allowing for high performing activities. 

How are Adaptive AI Systems created?

It uses Machine Learning, a type of pattern recognition process that allows this system to understand what it takes in. Sort of how humans learn math. They see the pattern of how to do the problem and do it over and over until they understand the topic. By looking at the patterns of data, it allows the system to look at the environment and adapt to it instinctively. As it gets new data over time, it starts moving through this adaptive AI System. It cycles through a process: automated data preparation, model and strategy redevelopment, model and strategy and review, and push button deployment leading it to the decision platform. This creates a self updating, fully automated cycle. You don’t need to build a static model rather this changing automated system allows us to have a clean feedback loop. 

What are the advantages of Adaptive AI Systems? 

  • Traditional AI needs human intervention to make these changes while an Adaptive system doesn’t. What takes a human months to do a machine can do in a fraction of a second. This makes a huge difference in productivity levels and the output a company can produce. 
  • Adaptive Systems can fit into any situation. Let’s give learning as an example. Say you want to learn math and you go on a website that tracks how you do and makes the questions harder/easier depending on your performance. Well this is done by adaptive AI systems. Through learning your data and responses, this system can take into account your progress and make a learning experience that is unique for you. 
  • This system continues to perform at higher levels compared to Traditional AI systems. 

What are the disadvantages of Adaptive AI systems?

  • With any AI system, it can lack creativity and originality. It is best to understand that with an automated and computer organized system there will be a lack of creativity alongside it. 
  • Adaptive AI can be quite expensive to start up. The initial investment can be substantial making this a tough financial decision for businesses.

With Adaptive AI systems, businesses can help create their productivity levels and output. With its ability to change according to its environment, adaptive AI systems are becoming highly useful for data collection. Next time you witness data adapting to your circumstance or seeing an awfully good customer service robot make sure you give credit to Adaptive AI. Adaptive AI Systems can help your company. Contact Data Ninjas to provide additional information or help you set up a demo. This addition can take your company to your next level, making the investment well worth it.

Consumer Data Privacy Law Trends: Why businesses are becoming more responsible for consumer data

Privacy is becoming increasingly important for members of society. As data is becoming more and more widespread, people are more worried about where their data is going, how it’s being used, and how it’s facilitated. As technology has been around for around a century, trends towards more privacy have been increasingly important. 

Data Privacy Trends

1. AI Governance 

There are many forms of threats that can hurt a company: one being a data breach or a hacker. With the risk of having data taken away, AI governance is becoming an increasingly important priority. It will help take in information about the patterns of consumers, employee behaviors and other key metrics. This way consumer data is far more protected by risks out of businesses control.

2. Centralized Privacy User Experience

People have started demanding more and more privacy rights. After case and case of data mismanagement, it is becoming an important ideal for many consumers. Therefore, many businesses need to create a portal with consent management for data. This way consumers have the option to allow management or disallow it. Either way, privacy UX such as cookies and notices can be more manageable when put under one page allowing for easier usage and better comprehension of data rules.

3. Privacy at home

As school was switched to virtual, jobs taken at home, and life completely shut down, COVID has changed the way data is used and regulated. Now that everything is centralized at home, privacy risks are becoming more paramount. Businesses should make sure they are not monitoring data 24/7 and keeping it to a minimum. By communicating and being transparent with the data used, employees can feel safe and secure with their data. 

4. Consumer mistrust 

Many customers mistrust businesses’ usage of data. They are often becoming more and more aware of the amount of data that is being mishandled. Often read in many fine prints in popular social media is the usage of personal data for things other than commercial use. This is becoming increasingly hazardous for typical data users. I mean take Facebook for example, they allowed around 87 million people’s data to get into other businesses’ hands. With their abuse of their stated terms and conditions, Facebook got sued with the mismanagement of consumer’s data. 

5. Government action 

With the increasing power businesses now have with data, governments have now taken it upon themselves to protect digital rights. By requiring companies to keep up with up to 27 online privacy bills, the government is taking a step towards our security. For example, according to The Washington Post, governments are “proposing a bill that would allow users to opt out of targeted advertisements and to sue internet companies that improperly sell their data.” This being one of the many bills being made, it is increasingly important that businesses start using consumer’s data in a more secure way. 

Texas State Level Laws 

  • Texas Privacy Act: Created in 2019, this act makes companies tell consumers whether their data was leaked, within 60 days and if it affected more than 250 people. 
  • Student Privacy Act: This act took place in 2017 and protected students’ data. By disallowing companies to use and sell student’s data, the student privacy act keeps our children safe from personalized ads and data breaches
  • Identity Theft Law: This law makes it illegal to steal someone’s identity. This forces businesses to make sure their company isn’t illegally used.

CCPA, California Consumer Privacy Act

  • It gives california consumers the right to know what personal information a business takes and how it is used or distributed 
  • Allows California residents delete their information collected from businesses 
  • Allows residents to opt out of selling their personal information 
  • Allows residents to non-discrimiantion if they use their CCPA rights 

Colorado Privacy Act

  • Requires businesses to include an opt-out function towards personal data usage 
  • Gives the right for consumers to opt-out from the sale of personal dta 
  • Gives the right for consumers to know if personal data is benign collected 
  • Allows consumers to fix/edit personal data
  • Allows consumers to delete their personal data 

Virginia Consumer Data Protection Act 

  • Gives consumers the right to see their personal data
  • Gives consumers the right to delete their personal data
  • Gives consumers the right to edit their personal data 
  • Gives consumers the right to opt out of giving personal data
  • Gives consumers the right to opt out of the sale of their personal data

Though just a couple examples of state level privacy regulation laws, it is becoming increasingly important to protect the rights of our children, our family and ourselves. 

Federal Level Regulation

As of right now there are no federal laws that control data privacy in the US. But there seems to be an increase in localized regulation such as in states and counties. The Federal trade commission act however has come to regulate some data, and enforce some privacy laws. However, it doesn’t explicitly state that in its purpose. 

With all this being said, consumer data privacy is increasingly becoming a big deal. Taking time to research and finding ways to secure consumer data can make your brand get more recognition and appreciation. To dive into data compliance in more depth check out our “Data Compliance – A Practical Guide”.

Governing ML Lifecycle metadata using Collibra

The video on this post shows how we used Collibra's metadata management and governance capabilities to manage a complete ML lifecycle. As metadata piles up in a data science organization around modeling, experimentation and data engineering, providing governance and intelligence capabilities is essential for long term management and oversight.

Adding role based permissions and using Collibra's workflow capabilities for approvals and promotions make it a complete solution.