Artificial Intelligence or AI as it is known is working towards autonomy and is functioning without human control. This type of autonomy is raising concerns over control over artificial intelligence. The competition within the AI among organizations is leading to the development of advanced algorithms that are raising questions of culture, ethics and principles for running AI responsibly.
The following five predictions about Artificial Intelligence are being predicted for the year – 2021 by the scientific community. These include-
- Customers are still wary of using Artificial Intelligence
Some of the customers or clients are still in a dilemma about using artificial intelligence on a daily basis. Users of Artificial Intelligence still did not know that by using free AI powered services they are giving up their data in return. There is a huge responsibility on governments and organizations to educate customers, or clients by introducing rules and regulations to protect them from the anticipated risks of Artificial Intelligence.
However, there is some evidence that over time such as within five years customers would eventually realizethat AI is influencing their lives. Then they would be in a position to ask challenging questions about AI causing companies to answer them.
- Digital transformation finding its way
The COVID-19 pandemic has resulted in implementation of drastic digital transformation plans. To adapt to the pandemic realities, organizations are forced to implement digital transformation at a faster pace after observing its reach out among the masses. During the post- COVID age, there will be more demand for AI automation and close monitoring of AI interactions. Hyper-automation can help streamline the process in the coming days.
- Companies will increasingly drive Artificial Intelligence to Edge
With increase in the capacity of computation and storage at the enterprise network edge, more computational power and functionality can be accessed. Chief Technological Officers or CTOs of organizations agree that extended edge use cases are highly dependent on AI’s maturation. This indicates a complementary collaboration between automation and machine learning.
The computing power is expected to increase with the proliferation of the IoT devices and the increased acceptance of 5G. Companies would want to ensure that everything synchronizes up to a central location. Eventually, isolating AI into edge computing silos will reduce AI’s power thereby pushing its limits.
- The questions about the governance of Artificial Intelligence
There would be questions raised about the governance of Artificial Intelligence as it becomes more prevalent. Stakeholders are rising to the challenges that AI poses to the public resulting in the organization being forced to provide responsible, open, and impartial AI systems. However, the big question is about who will ensure that this occurs and is regulated. Government, business groups or any combination of these.
In case, the organizations come forward to take action to ensure fair and impartial data that feeds their AI then these models should be empathic, open and robust.So far, some of the organizations are still lagging in providing the model code of conduct while using artificial intelligence. Nevertheless, there is aneed for government authorities or regulators to introduce policiesabout thegovernance of artificial intelligence.
ModelOps reaching the tipping point for operationalizing AI models
In 2021, it is expected that ModelOPs will assist organizations everywhere to strike the right balance. With ModelOps, more enterprises are expected to efficiently push their AI models up the food chain. This process is expected to agile, creative and not restrictive especially with the citizen data scientists.
Lastly, it can be said that with AI becoming more wide spread it is likely to create more structure and controls around AI processes and policies. As such, AI can benefit customers and companies if used and handled wisely.