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How AI And Ethics Will Affect the Future Workplace

Touching every sector of organizational processes, Ai is heralded as the technological advancement that will finally usher in a new dawn of computing to push the world firmly into the 4th industrial age. However, with this great promise comes pertinent questions on the ethical challenges surrounding AI applications. These questions touch on matters such as job security, human safety, cultural alignment, and in a more distant future, the very existence of the human species in a world of autonomous AI. While AI technologies are currently in their infancy, jump-starting conversations around these issues is crucial to preempt crises that may arise well after Pandora’s Box has been opened.

We spoke with three experts, Dr. Maya Ackerman, Vaibhav Pahwa, and Siobhan Neilland on how AI and ethics will affect the future workplace.

Watch an In-depth Webinar on The Impact of AI and Ethics on the Future Workplace by Dr. Maya Ackerman, Vaibhav Pahwa, and Siobhan Neilland

In this in-depth webinar, follow along with the three experts as they discuss the various issues that AI and ethics will raise as the future workplace transforms.

Creativity and Co-Creation

Dr. Ackerman, assistant professor at the School of Engineering, Santa Clara University and founder of ALYSIA, an AI platform that assists in the creation of songs, sees AI as acting more as an enabler rather than a replacement for humans. This crucial observation attempts to remedy the heated discussion that currently surrounds the rise of AI and the possibility of job losses associated with an automated robotic workforce. While the discussions are legitimate and require extensive public participation, Dr. Ackerman sees AI as more of a sidekick to human efforts rather than a replacement of humans. She alludes to the fact that while computational creativity is rapidly advancing, it still stops short of fully autonomous creation.

For a computer to be a fully autonomous creator, she says, it must first create and then evaluate its creation. This critiquing would provide AI systems with the same set of tools that a human creator has. However, current AI creators have extensive capabilities regarding creation but cannot evaluate these creations. Dr. Ackerman sees this as an opportunity for man and machine to collaborate, as is the case with communications platform Slack and Slack bots. She says that this synergy has the potential to unlock levels of human potential currently unavailable. She gives the example of Garage Band, a popular tool used to create instrumental sounds. While this resulted in fewer people using actual instruments to create music, it has opened a new level of creativity where people are using technology to synthesize sounds that would have been impossible to create, at scale, with physical instruments.

Ethics and Inclusivity

Current AI is built on machine learning algorithms that use historical data to build predictive models from which to draw from when computing real-world challenges. However, this data is gleaned from deeply biased sources, bringing with it the baggage of human biases. This results in the development of biased AI that propagates the biases humans are currently encumbered with. Vaibhav, head of product and engineering at Atipica, sees this as an important aspect an AI builder must consider in ensuring the systems they build do better than humans when it comes to ethics and inclusivity. To achieve this, Vaibhav sees human intervention as an important aspect of training AI.

This sentiment is echoed by both Dr. Ackerman and Siobhan who both see a pressing need for humans to play a greater role in building ethics and inclusivity into AI and not just leaving AI to draw its own conclusions based on the data. Dr. Ackerman, for instance, has opted to intentionally hire individuals to her team in a manner that fosters inclusivity and balance, something she says an AI would struggle to do because most are optimized to find the best candidates and not necessarily pick one over another to compensate for inclusivity and balance.  Vaibhav echoes these sentiments by pointing out that organizations should use AI to understand better and anticipate their hiring needs rather than focus on how to use AI to automate bottom-line-focused tasks.

Human-centric Data Parsing

Siobhan, chief executive officer of and a senior leadership consultant at SER Consulting, sees this disconnect between AI and the need for a more nuanced approach to work in her work as a recruiter for tech behemoth Amazon. She has noticed that, for instance, an AI, when scouring the web for potential candidates for a position, will select those with certain conventional traits. These traits point to a typical career path leading up to the position being recruited for. However, by intentionally looking for candidates with asymmetric career paths leading up to the position, she finds non-typical candidates who fit the position. This candidate pool tends to be more inclusive of women and minority groups.

From an AI perspective, Siobhan sees this as a fundamental flaw that must be fixed. She notes that while AI is great at picking typical candidates, most AI is not optimized to find outliers. This non-human-centric means of data parsing means biases and typical hiring trends are propagated, leading to the continued marginalization of women and minority groups. She also explains that most candidates struggle to perform well at interviews because they have been subjected to rigid AI-based recruitment algorithms in the initial stages of interviewing, which do not allow them to properly demonstrate their strengths. These systems do not compensate for cultural issues that are crucial to finding the right candidates, especially for senior positions. As a result, she says until AI grows beyond its current constraints there is still a need for human-initiated interventions.

Here To Help, Not Replace

Dr. Ackerman, Vaibhav, and Siobhan are all optimistic about the future of AI in the workplace. They see AI as playing more of an enabler role than one of replacement. They are, however, insistent that for AI to truly take its place in the future workplace, it must have built-in ethical, inclusivity and co-creation traits, traits that will essentially make AI more human and less machine. However, this future AI depends on the time and effort AI builders and organizations put into teaching AI these traits in order to enhance human recruitment efforts, and not only focus on getting AI to supersede humans with a short-sighted goal to displace the labor cost of recruiting and maintaining a human workforce.

In this in-depth webinar, follow along with the three experts as they discuss the various issues that AI and ethics will raise as the future workplace transforms.



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