Early sketches of the future Artificial Intelligence (AI) painted it as machines with ultra-human abilities.
How is AI used today?
AI was heavily conceptualized in its early days as a heavily automated machine with the capability to “take over the world”.
However, that image is far from the truth of its common usage. An example of the use of AI is the implementation of “Alexa”.
Prior to its invention, a speaker was simply used for what it was: a speaker.
The implementation of AI technology in the Alexa product has transformed an everyday speaker into an all-knowing machine that accurately answers any question and performs multiple daily-life tasks.
The power of AI has grown such that AI systems are able to autonomously make decisions. This means that they are not simply passive machines; they are indeed capable of performing a task or decision solely based on the matter at hand.
This capability is variable: it changes according to the data training it has received and the specific functions of its programmed algorithm.
What are some controversies surrounding the use of AI?
These main functions have left some people wondering what comes next with AI. It is easy to fall prey to intimidation of AI’s intelligence, capability of intentionality, and human-like problem-solving skills.
Several concerns and challenges regarding the use of AI include the issue of determining the correct data set and the ensuring data privacy concerns and finding highly skilled people who are knowledgeable about training AI systems.
AI relies on large data sets in order to learn specific functions. It can be difficult sometimes to obtain optimal and high-quality data sets. Training AI systems with poor-quality or limited data can sometimes result in systems that employ biases.
These biases include racial and discriminatory pattern learning.
Another concern about the growth of AI pertains to the issue of data privacy. Because AI relies on large data sets to assess and “learn” patterns, it is important to ensure that data usage and storage stays ethical.
User access to large data storages should be carefully considered, for the more access users have, the more prone it is to leakage or unethical abuse.
A challenge imposed by AI is the need to train people with the specific programming and algorithm-creating skills to set up AI systems.
If specialists are not properly trained to develop AI systems, issues in AI infrastructure or accidental misuse of data can occur.
It is understandable to be concerned over safe and ethical data management and AI-system development. Looking towards the future, it is imperative to ensure trained specialists store and handle data with care.
This can ensure a safe employment of AI in our near future.