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Harnessing the power of augmented intelligence

The majority of organisational data is unstructured, and has no pre-defined data model or is not organised in a pre-defined manner. This lack of structure creates challenges in data governance, and in harnessing the potential value that can be derived from the data.

The aim of augmented intelligence is to make sense of this data, by quickly providing data-driven insights and correlations in a business context that the decision-maker can understand and action. The context is aided by the analytics-driven categorisation of vast amounts of information and the identification of themes or subjects relevant to the business context of the user.

"This allows the decision-maker to quickly understand the data, perform contextual data discovery and draw insights," says Lyle Petersen, Business Intelligence Business Analyst at Woolworths, who will be presenting on ‘Man with Machine: Harnessing the potential of augmented intelligence', at the ITWeb Business Intelligence Summit which is being held at The Forum in Bryanston, on 13 and 14 March 2018.

What is augmented intelligence?

According to Petersen, augmented intelligence involves systems that enhance the human ability to find insights. "It is a symbiotic relationship between the human decision-maker and machine driven insights – aiming to combine the best abilities of humans with the current advantages of machines."

He says it consists of data-driven approaches such as machine learning, natural language processing and pattern recognition. These data-driven solutions are there to aid human decision-making, by offering insights and correlations that understand and action.

"Human interaction is another key factor in an augmented intelligence system. The solution has to allow the decision-maker to easily interact with insights in a meaningful business context and to be able to leverage intuition and experience to make sense of the newfound knowledge. It is when new insights are combined with human experience and existing insights from a variety of sources and stakeholders that true business value is found."

AI vs AI

Lyle Petersen, Business Intelligence Business Analyst at Woolworths.

Lyle Petersen, Business Intelligence Business Analyst at Woolworths.

Speaking of the difference between augmented intelligence and artificial intelligence (AI), he says the latter, in the traditional sense, refers to systems which imitate human intelligence by attempting to think, use logic and reason autonomously. "These goals, however, have not yet been fully realised. Our current artificial solutions do not think for themselves. Machine learning, which is the mostly widely used artificial intelligence technique, is only as good as the intelligence fed to it by humans."

Augmented intelligence realises the current challenges of AI, including inherent biases which may occur in algorithms or poor data provided. "Other challenges include difficulties in dealing with complex decisions such as ethics and moral dilemmas. It differs from artificial intelligence by not being an autonomous solution but rather enabling humans to interact with aspects of artificial intelligence to make holistic decisions – being able to question correlations in data and draw strategic hypothesis. The human maintains the driving seat by making the ultimate strategic decision."

Faster speed to insight

Petersen says the application of augmented intelligence can benefit the business in many ways. "The first is in the lowering of risk. There is inherent risk in relying solely on machines including the risk of poor data and biased algorithms being used in data-driven endeavours. The human factor serves to mitigate this risk by leveraging on inherent experience and collective judgement to ascertain whether correlations make sense."

He adds that it relies on contextual data analysis with an intuitive user interface, which allows a business user to engage with insights, and empowers them to make that next step in the decision-making process. "This leads to the democratisation of data in the business, and empowers more users in the enterprise to operate like data scientists – leading to better strategic and tactical decisions at all levels of the enterprise."

Combining human and machine capabilities leads to a faster speed to insight and the potential discovery of insight with far greater strategic value, explains Petersen. "Machines are masters at collecting and correlating information leading to new insights. At this point humans are still better at higher levels of reasoning, judgement and strategy."

In addition, he says machines excel at specialised analytics tasks that are geared toward a specific purpose, while humans can more easily combine the learnings from a variety of experiences, incorporate insights from a social context and strategically ‘think out of the box'. "It is when we holistically combine these abilities of man and machine that we reach a new level of discovery."


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