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DATA DEEP DI V E

Cognitive computingThese findings are based on an independent study of 1200 IT influencers from a mix of large and small companies across Europe.

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What is cognitive computing and how is it really being used at the moment?

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The whole idea of a computer that thinks for itself is inherently scary for most humans, so it stands to reason that we are bombarded with movie plots and stories about artificial intelligence taking over the world. Therefore, any survey that attempts to address the potential impact of cognitive computing has to take into consideration the misconceptions and the blurring of the edges between the singularity and a sophisticated data analytics engine. Most people have an opinion about AI even if they don’t really understand it and this impacts views on the whole idea of cognitive computing.

While luminaries such as Elon Musk focus on AI and futurology – Musk recently announced he’s developing a product to make anyone superhuman1 – cognitive computing has, for the foreseeable future, a more mundane role to play in everyday life but ultimately an extremely useful one. By enabling a computer built with machine-learning algorithms to ‘learn’ from vast quantities of data, identifying patterns and suggesting possible actions, cognitive computing has the potential to solve some extremely complex problems.

“Cognitive computing is basically automation on stilts and it will slice through repetitive, time consuming

operations.“ – survey respondent

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One of the best-known cognitive computers is IBM’s Watson, which made its first major public appearance on the US TV show Jeopardy! in 2011, beating two legendary champions2 to the $1m first prize . Today we are already seeing Watson helping to predict the weather3

and improve healthcare, including drug discovery4 . It’s a rapidly developing field with Google DeepMind, CognitiveScale and Microsoft’s Cognitive Services just some of the businesses researching and developing ‘thinking’ machines. Given the amount of data being generated in almost every industry – there are 2.5 quintillion bytes of data created each day at our current pace5 – we will need cognitive computers to make sense of it all. Otherwise, what is the point?

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What impact will this technology have on the workplace in five years’ time?

Unsurprisingly a third of respondents believe that cognitive computing will have the biggest impact of all technology trends on their business in the next five years. It’s a fair assumption given the rapid rise of machine learning and the proliferation of data delivered through devices and IoT networks. Determining whether this impact is positive or negative however, is not so easy because in the majority of cases it will be both.

The idea that automation through more intelligent machines will destroy jobs continues to hit the headlines. A recent OECD study6 , suggests that 47% of US jobs and 35% of UK jobs are “high risk” so understandably people are going to see cognitive technology as a threat. However, it is also an opportunity to augment existing work. In combination with IoT data, for example, cognitive computing has the potential to generate insights into everything from traffic analysis through to design faults in wind turbines and suggest solutions. For many people, cognitive computing will not only make their jobs easier, it will make them more dynamic and innovative, regardless of industry.

INTERNET OF THINGS

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BLOCKCHAIN QUANTUM COMPUTING

COGNITIVE COMPUTING

IMMERSIVE EXPERIENCE

49%39%

35%29%

25%23%

*Based on the percentage of professionals who rated the impact of each of these technologies as 5 or 6 out of 6

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“A machine that can reason and deduce without the clutter of

emotions to distract or influence will obviously be more efficient and besides, nothing will work in the

future without artificial intelligence.” – survey respondent

Which technology trends will have the most impact on the workplace over the next five years?*.

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Will cognitive computing make us more productive?

The survey is unequivocal when it comes to the question of productivity. A resounding 45% of respondents believe it will increase productivity, but of course this comes with caveats. For a start, cognitive computing will make some more mundane administrative roles redundant. For the most part it’s not a primary function. Organisations will look to cognitive technology to solve complex problems and increase competitiveness through innovation, increase security or improve personalisation of products and services. Much of the work will augment existing roles or create additional work above and beyond traditional practises.

I don’t knowLess productive More productive Stay the same

“A lack of understanding of the technology will result in a hit in productivity due to the

learning curve, then there is the cost incurred with such technology making it

prohibitive which in turn makes my organisation less productive in comparison

to others able to afford it.” – survey respondent

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15%

15% 45%

35%

What impact will cognitive computing have on workplace productivity?

Respondents from large companies are even more likely to believe that productivity will be boosted (51%). And this rises further in large French companies (59%). This makes sense from a data scale point of view. More data roughly equates to an increased chance of more accurate analysis and better insights and actions. A large supermarket, for example, would be able to get a better understanding of customers in a town than say a small convenience store. It’s a question of scale.

Of course, how businesses use the data and ensuing intelligence will vary and human interpretation will no doubt determine how useful or successful the cognitive analysis actually is. Does this mean

individuals will be more productive or does it mean organisations as a whole will be more productive, agile and efficient?It will take time that’s for sure. As over a quarter of respondents suggest, productivity will probably stay the same for the next five years and as a whole they may be right. There is certainly the skills issue to consider here. It will take time to learn new systems and for individuals and departments to create and manage new processes. So, in some ways, productivity could go down before it goes up again, at least within five years. Some departments though are almost certainly going to see change sooner. Healthcare research in particular is one area where productivity gains will always be welcomed, and that, for the moment at least, seems to be a particular focus.

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What is holding the technology back?

A lack of data is almost certainly not an issue, although 21% of people believe that a lack of understanding of the technology is an issue.

Overall almost 50% of respondents felt that it was either the actions of senior management towards implementation or employee behaviour towards the technology that was holding it back. There are clear reasons why.

Firstly, cognitive computing is still new and applications are not exactly plucked from the shelf. The cost and disruption of implementing cognitive computing systems will need careful consideration and planning, especially for established businesses

“Most of the workforce will be against this through fear of being replaced and not understanding it

properly, and therefore will not attempt to work effectively with it.”

– survey respondent

14%21%24% 18%

Lack of understanding about the technology

Don’t knowEmployee behaviourstowards the technology

Internal business processes

24%

Actions of senior management regarding implementation

Which factor is most likely to prevent cognitive computing from being incorporated in the workplace?

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with legacy systems. Can cognitive systems multiply production and profits for example? Where are the use cases?

Secondly, businesses with labour-intensive processes and a digitally-challenged workforce will have to go through an extensive re-training or talent acquisition program, not something that is achieved quickly and easily.

Establishing a clear roadmap with worthwhile and yet achievable goals is difficult to draw, especially if it impacts jobs and requires new skills. Demystifying cognitive computing and improving industry-specific, cloud-based solutions will go a long way to helping make this more palatable.

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What conclusions can we draw?

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The rate of adoption will depend on the vertical industry. In healthcare and cybersecurity, for example, cognitive computing is already making great strides and as Howard Roberts, Technologist at HP suggests, “we are at the tipping point for the technology”.

The ability to crunch unbelievable amounts of data will make elements of cognitive computing, such as machine learning, increasingly essential. Machine learning is already used in fraud detection systems and in oncology and security software makers are exploring its use in advanced malware detection systems.

“The fear that people have is not surprising as cognitive computing is equated with automation and job losses,” says Roberts, “but the reality is that we will see an increasing use of cognitive tools embedded in facial and image recognition systems, for example. It will evolve at different rates in different industries but it’s already here and doing some amazing things. We just have to ensure we educate users and reskill the workforce to enable it and make better use of the opportunities it will inevitably create.”

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Appendix

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This research was conducted by Spiceworks on behalf of HP. The 1200 respondents came from job titles ranging from helpdesk to CEO, in companies ranging from under 50 employees to over 5000 employees, from UK, France, Germany, Italy, Spain, Nordics, Benelux. The full breakdown can be found below.

1. https://www.cnbc.com/2018/09/07/elon-musk-discusses-neurolink-on-joe-rogan-podcast.html

2. https://www.youtube.com/watch?v=P18EdAKuC1U

3. https://www-05.ibm.com/uk/weather/

Links:

Breakdown of respondents by company size Breakdown of respondents by country Breakdown of respondents by job title

Company size

<500

500+

Dataset

588

612

Country

UK

France

Germany

Italy

Spain

Nordics

Benelux

Dataset

200

200

200

200

200

100

100

Job Title

Owner/CEO/President

VP IT/CIO

IT Director

IT Manager

Network Architect

Network Admin

Help Desk

Tech Consultant

Other

Dataset

120 (10%)

108 (9%)

204 (17%)

300 (25%)

24 (2%)

192 (16%)

72 (6%)

108 (9%)

72 (6%)

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4. https://www.healthcareglobal.com/technology/four-ways-which-watson-transforming-healthcare-sector

5. https://www.forbes.com/sites/bernardmarr/2018/05/21/how-much-data-do-we-create-every-day-the-mind-blowing-stats-everyone-should-read/#3766c0fa60ba

6. https://www.oecd-ilibrary.org/fr/employment/automation-skills-use-and-training_2e2f4eea-en