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By Irina Farooq, Chief Product Officer at Kinetica

Ethical AI Starts with Data

Artificial intelligence is on the rise, and deploying AI with ethical practices in place will need to be a key priority over the course of the next decade. Irina Farooq, Chief Product Officer at Kinetica, believes that to employ an ethical framework, businesses must first educate themselves and their workforces about data best practices.

2010 to 2020 saw the rise of artificial intelligence. For the first time, businesses began to recognize AI as the next wave of innovation, and now we're at a point where businesses believe they must leverage AI in order to be leaders in their industries. But the reality is, while everyone has been so quick to roll out AI-enabled technology, not everyone has been successful at it. 

Business leaders are shifting from a mindset of "I need artificial intelligence" to "where and how can AI be most useful?" But in 2019, we saw far too many examples of what can go wrong when you deploy AI--as Goldman Sachs experienced when a tweet about an Apple Card went viral. As we look towards 2020 and beyond, businesses will need to assess their AI implementation, and ask not just "how is this useful," but also, "how can our business ethically develop our AI technology by implementing or adjusting internal protocols?"

Data is the most valuable business asset today. It's at the core of AI and machine learning (ML): data in, AI-powered decisions out. But many organizations do not fully understand their data, and thus are unable to identify business challenges accurately. AI and ML efforts cannot be deployed effectively unless data has been assessed properly. 

So what's next? To start, businesses will need to invest in educating their workforces about AI, ML, and data analysis. As reliance on AI technology continues to grow over the course of the next decade and beyond, we're going to see data scientists become a key part of the software development team, along with product managers, QAs, and the software developers themselves. Data scientists will bridge the gap, helping their teams better understand data in order to address challenges ethically, while optimizing outcomes. 

As the Fourth Industrial Revolution continues to thrive on data and becomes increasingly reliant on AI-enabled decisions, it will be more crucial than ever that businesses implement ethical AI best practices in 2020 and beyond. From the development process to deployment, the only way we can address the growing concern around ethical AI is to work from the inside out. Adding a data scientist to your team opens the door to understanding how to strategically, ethically, and effectively build data sets. AI is here to stay, so as we look towards a new decade, it is our responsibility as business leaders to prioritize ethical practices. 

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About the Author

 

Irina is Chief Product Officer for Kinetica. Irina has over a decade of product management experience across a variety of sectors, including enterprise software, networking, hardware, IoT, SaaS, and Cloud. Irina joins Kinetica from Riverbed Technology, where she held a variety of leadership roles including Vice President of Products and Strategy for the Service Provider Business and Vice President of Product Management for Steelhead, Riverbed's flagship product. Prior to Riverbed, Irina was Vice President of Embedded Systems for Grid Net, a Smart Grid/IoT company, where she was responsible for engineering and product management of the company's hardware and firmware. Irina started her career as a software engineer and product manager at Oracle. Irina holds a B.S. in Mathematics and a B.S. in Computer Science from MIT, an M.B.A. from Stanford Graduate School of Business, and an M.S. in Environment and Resources from Stanford University.