Why human oversight will be essential to the next generation of automated data anaytics
We’ve all read the news and heard the scaremongering stories around potential flaws and biases in Artificial Intelligence (AI) systems. Despite the scepticism, businesses are undoubtedly using the technology to streamline work processes, automate timely tasks, and completely reimagine the way individuals work altogether.
But to truly harness the potential of AI, we need to move past the speculation and foster a workforce that unites the power of both humans and emerging technologies. ‘Augmented Intelligence’ spans across business intelligence and automated data analytics, and encourages businesses to put human intuition in the middle of data analytics and advanced algorithms.
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Human-led yet ‘autonomous’
Currently, AI innovation is at its peak, with numerous business intelligence and data analytics technologies springing up each week. It is a sector that is rife with competition and with a thirst to constantly innovate. With the number of impressive machine learning algorithms being implemented across the globe, it is easy for businesses to want to be ahead of their competition and to then challenge one another with the development of an even more impressive AI, BI or data innovation.
However, this hunger to continuously innovate and out-do the competition brings the risk of businesses building intelligent systems that sway too far away from what we really intend for AI to do – to make our lives easier as humans and enable us make quicker, fairer and unbiased decisions. Wasting time building innovative tools that are shiny yet impractical could lead to the development of flawed tools that attempt to solve imaginary problems.
When developing autonomous technologies, we must remember to keep humans in mind. Not just in terms of the end goal, in which we try to visualise how an AI innovation could assist with our day to day lives, but by remembering how a particular AI system or algorithm can be built to function alongside human intuition. Autonomous AI technologies must be always developed with a goal of being an assistive technology – not one that replaces.
However, the development and implementation of AI innovations with a key purpose in mind will also ensure that their future use in the workplace and beyond adheres to modern government policy and regulation. With the GDPR in full force and many public sector organisations – such as the police – facing scrutiny over the use of intelligent technologies, keeping humans close to the development, use and regulation of our AI tools will minimise the room for fault.
Data governance to drive business success
Data governance, however, is not just about adhering to regulation. With AI innovations fuelled by enormous data sets, governance therefore has a close relationship with how EU organisations can drive business success through AI implementation.
The idea of trust supports this relationship between data governance and business success. Trust is a fundamentally human feeling that cannot be replicated by an autonomous technology or advanced algorithm. In the healthcare sector, for example, where data is particularly sensitive, building this trust between technology and patient is no mean feat.
With vast amounts of data coming from multiple disparate systems, an effective data governance strategy within EU organisations also becomes important for AI to produce trustworthy insights. Data governance offers a simple and direct way to ensure that the right data is used to generate insights, but also identifies data errors and quickly flags and resolves those errors to help maintain an organisation’s confidence on data and ultimately on the insights generated.
To take this confidence one step further, a data catalogue integrated with data governance, for example, can empower EU organisations with a quick and efficient insight discovery, meaning that data users spend less time searching for the trusted data they need to feed into AI. This not only speeds up internal results brought by the use of advanced AI technologies, but will help the overall EU market achieve a greater level of digital transformation in the race to become a global AI leader.
Trust equals value
AI is having a huge impact in all markets and business domains but if we are not careful, the immediate hype will undermine the long-term opportunity available for the EU’s digital transformation. AI in the context of analytics and data is ultimately about making the path to insight quicker and more accessible to more individuals. However, AI and analytics in practice relies on trust, and without it, all efforts to transform into a digital-first continent will be valueless.
Automated data analytics must be combined with human intuition – particularly as the capabilities of AI grow in complexity. Data sets, however refined they may become, will always require human oversight for any resulting decisions to be fully informed and accurate. Undoubtedly, this human oversight is essential to ensure that data and all associative ‘intelligent’ technologies always adhere to government policy. This is vital to help pioneer innovation as the EU undergoes a significant digital transformation.
Elif Tutuk, Director of Research at Qlik
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