A technology that promises to contribute nearly USD 15.7 Trillion to the global economy by 2030, one that is expected to drive worldwide spending of USD 57.6 Billion in 2021 alone, Artificial Intelligence (AI) has truly transitioned from its tag as a future tech prodigy at the beginning of the 21st Century to the driver of future tech as we enter into the second decade of the same century.
As we look around, the applications of AI abound in almost every consumer sphere. From curated recommendations, while shopping on Amazon to Google Now and Siri playing favorite tracks on a user’s voice command while driving, the target areas of impact for AI are very vast today. While shopping and music playback are popular examples, today we have other critical areas where AI takes center stage. These include credit card fraud identification, crime prediction through algorithmic criminal risk assessment, intelligence surveillance through facial recognition on video feeds from public cameras, and much more.
With more government agencies, businesses, and individuals rolling out newer use cases of AI, the old Man Vs Machine debates have sprung up in parallel. The possibilities of the events unfolded in the Terminator movie saga are still years or decades away from being considered a threat, but there are concerns about relying on machines for decision-making. AI systems can indeed provide unbiased decisions or inferences, but the problem lies in the training data to learn from as historic data could have biased human judgments too as their base.
The problem lies not in the technology but in the way it is governed. A recent PWC survey found that only 25% of organizations have prioritized ethical implications for their AI initiatives. The ability of AI to scale up and amplify a marked behavior can be a recipe for illegitimate market or consumer influence.
The rapid pace at which companies use AI to deliver more offerings for consumers without having an eye out for enabling ethical implications is a dangerous precedent that needs to be corrected.
So now comes the big question – How can AI initiatives be made more ethical and responsible? Let us have a look at these tips
As AI is significantly impacting the way companies perform across departments and customer channels, the foremost step that businesses need to take is to promote a culture of transparency in their AI initiatives. Studies have shown that 84% of business leaders opine that decisions arrived at with the help of AI systems need to be explainable. There is no scope for ambiguity to exist as all stakeholders should be able to access the fundamental basics of how an AI system arrived at a particular inference. It may encompass, the training data from which it learned, the neural training models used, the contextual factors are taken into consideration by the system during the processing, and much more. The more transparent an AI system is, the more trustworthy will it be deemed.
Create a Risk Assessment Framework
For every business that is moving in a direction to utilize AI for a significant value realization in their offerings, it is important to first create a risk assessment framework. This framework should encompass ways to identify potential risks that may occur when AI is implemented. Have a detailed mitigation plan to minimize or eliminate the risk, the people who must collaborate from different departments to identify risks, their solutions, and the necessary technology tools or platforms that need to be made available at different levels of assessing and mitigating the risk.
While in the initial days, AI was perceived as a threat to the human workforce, it has now matured into being one of the most sought-after workforce augmentation and empowerment technology in several sectors. From helping marketers drive more targeted campaigns to enable clinicians to make more informed diagnostics, AI is augmenting human intelligence with scale, speed, and superior inference models to help predict real-life outcomes in various scenarios. When advancing with AI augmentation, companies must ensure that their workforce is well versed with the societal and ethical compliance any joint effort with AI needs to follow. The framework discussed earlier for risk identification and mitigation needs to be made a mandatory element of employee training sessions. Operational policies should lay out the guidelines for human-machine collaboration in the decision-making process of the organization.
Close supervision by a human workforce that is equipped to deal with solutions to challenging problems, is a necessity when it is being trained to autonomously deal with such situations in the future. Algorithms need to be periodically evaluated for effectiveness, end-user feedback needs to be continuously integrated for a better experience, and a whole range of accountability, bias control, and security policies need to be enforced continuously.
Nearly 83% of all businesses consider AI to be a strategic priority to grow their reach. From better marketing to improved employee engagement, the need for AI is far more than ever now. However, given the freedom, there should also be an assurance that every AI initiative that a business introduces is ethical and holds the responsibility to deliver an unbiased decision or action for all stakeholders.
Article by: Anand Pansare