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Will a robot take my job?

Recent research has found that AI has the potential to double the growth rate of the South African economy. Even though this is great news, it is worrying for many employees as they begin to wonder if they will be replaced by a robot, says ROB JARDINE, Head, Research and Solutions at the NeuroLeadership Institute South Africa.

Last year, research by Accenture and the Gordon Institute of Business Science (GIBS) posited that artificial intelligence (AI) had the potential to double the growth rate of the South African economy and boost rates of profitability by an average of 38 percent by 2035. This is great news for South African businesses of course, but an AI-dominated landscape brings with it multiple ethical and social issues, including the problem of a labour force that feels redundant and whose skills may be no longer needed.

AI will undoubtedly change the world of work, just as the Industrial Revolution did in the 1700s and 1800s. Certain jobs will become obsolete, as intelligent machines will be able to complete tasks quicker and more accurately than humans. New roles will also be created – jobs that we haven’t even thought about yet. AI will be the biggest disruptor the business world has seen in over two centuries. It is little wonder, then, that people are already starting to get jittery about the possibility of being replaced by, or working with, a robot in the near future.

Why we see AI as a threat

Neuroscience, which focuses on how the brain works, has some valuable insights into precisely why AI is perceived as such a threat by the workforce. As social animals, our desire to be part of a herd – in this case a company – is hardwired into our brains, an evolutionary remnant of when physical survival depended on safety in numbers. Any sense of social exclusion, therefore, is felt as a danger to our very existence, and our brain is consequently sensitive to this trigger in our social environments.

Feeling excluded is one of the five social triggers that is interpreted by the brain as a result of its central organising principal: to minimize danger and maximise reward. These triggers can put our brains into a threat or reward state that has an effect on our capacity to solve problems, make decisions and collaborate. AI is particularly threatening because it can be triggered by all five areas of human social experience: Status, Certainty, Autonomy, Relatedness, and Fairness (SCARF ®).

AI threatens an employee’s Status, as their value in the workplace and as a productive member of society comes into question. Certainty is no longer guaranteed, as the future is unpredictable and employees wonder whether they will even have a job in the next five years. With AI encroaching on the workplace, employees feel as though they are losing their Autonomy because they cease to feel in control and think that they may not have options. Their Relatedness is threatened as they believe that they don’t belong anymore and are not sure which group they may belong to in the future. Finally, a sense of Fairness is triggered in employees as they feel as though they may not be treated equally.

One of the worst effects of being in a threatened state is that people are not open to change because the brain has less access to long-term memory and its capacity to think rationally and make decisions is reduced. This is because the brain is in a flight-or-flight survival mode, and so does not prioritise these actions. People are consequently also unable to see AI as something that could allow them the space to be more innovative, explore a new career, or give them more free time.

This brain state also affects the control of self-defeating behaviour; for example, an employee in a threatened state could stop being collaborative with their colleagues, procrastinate in their work, and have lower capacity to solve problems. None of this behaviour is conducive to doing business or ensuring a productive workforce.

Cultivating a growth mindset in employees

As AI becomes more of a permanent fixture in companies, employers should start focusing on fostering a growth mindset in their employees, so that they welcome the change that AI will bring, rather than fearing it. This mindset, pioneered by the work of Dr Carol Dweck, is based on whether employees believe that their abilities are finite or if they can be developed. If they do believe that their ability can be developed, then they will be inspired by the change and look forward to it as an opportunity to grow.

We must also remember that, with the dawn of the age of AI, human qualities become far more valuable. AI machines cannot truly collaborate and adjust their behaviour in relation to others’ actions. They do not have the same degree of social intelligence, and cannot become leaders. AI machines also lack business acumen and are unable to transfer their ‘skills’ from one industry to another. All these qualities, even in the age of AI, will still be a vital aspect of ensuring a prosperous society and thriving economy.

Entrepreneurship provides a solution

It is undeniable, however, that many South African’s jobs will become obsolete or change as AI becomes more of a permanent fixture in the workplace. The significant portion of SA’s workforce that is unskilled or semi-skilled will most likely be the first to be replaced by machines that will be able to do the work more efficiently. This will place pressure on individuals to change how they approach work and possibly to seek work in other sectors. However, this is no different to how jobs have evolved in the past. The introduction of more efficient farming technology a few centuries ago, for example, meant fewer people were needed to farm the land and so more workers were able to take up roles in other industries where there were labour shortages.

But with every door that AI closes to the workforce, another one opens – in this case, entrepreneurship. AI will make entrepreneurship an even more sought-after skill in the SA economy, as it focuses on innovation, provides employment opportunities, and has significant social impact. Entrepreneurship also gives individuals a sense of belonging, as being productive members of society provides Status, Certainty, Autonomy, and a sense of Relatedness and Fairness. People are able to elevate their level of contribution, they have more certainty and autonomy in their own work in an entrepreneurial setting, and can develop a more individualised sense of belonging by being able to gain as much as they contribute. This sense of belonging means that people are performing at their best, as they do not feel threatened by a change that may seem out of their control.

Of course, in order to retain employees, it is not feasible to ask them to set up their own shops. However, as employers, we can look at the ways that we define and integrate current employment when the machines join us in the workforce. By allowing employees more autonomy and control in the way they do and view their work, we can put them in a better brain state, as it plays to their social drivers. In most industries where the impact of machines will become more prominent, this is already being done in the advancement of the gig economy.

In conclusion, then, AI is definitely set to change our workforce in the next few decades, but not all these changes will be threatening. It is up to employers to ensure that their employees realise this by playing to the social domains that trigger the brain, so that every individual can continue to perform optimally, learn new skills, and work towards their future roles in stimulating our economy. If we are able to do this, we will ensure our brains will be at their best to face and embrace this change.

In a world that is becoming more mechanistic, it is our ability to be aware of our social surroundings that both sets us apart, and allows us to never fear a robot taking our job.

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Now IBM’s Watson joins IoT revolution in agriculture

Global expansion of the Watson Decision Platform taps into AI, weather and IoT data to boost production

IBM has announced the global expansion of Watson Decision Platform for Agriculture, with AI technology tailored for new crops and specific regions to help feed a growing population. For the first time, IBM is providing a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and IoT data to help give farmers around the world greater insights about planning, ploughing, planting, spraying and harvesting.

By 2050, the world will need to feed two billion more people without an increase in arable land [1]. IBM is combining power weather data – including historical, current and forecast data and weather prediction models from The Weather Company – with crop models to help improve yield forecast accuracy, generate value, and increase both farm production and profitability.

Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska, said: “As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions. For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.”

New crop models include corn, wheat, soy, cotton, sorghum, barley, sugar cane and potato, with more coming soon. These models will now be available in the Africa, U.S. Canada, Mexico, and Brazil, as well as new markets across Europe and Australia.

Kristen Lauria, general manager of Watson Media and Weather Solutions at IBM, said: “These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and IoT sensors affixed to combines, seeders, sprayers and other equipment. Most of the time, this data is left on the vine — never analysed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crops.” 

The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 2036 [2]. Applying AI and analysis to aggregated field, machine and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers. The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.

The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help a livestock company eliminate a certain mold or fungus from feed supply grains or help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could help deliver the perfect French fry for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.

Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.

IBM and The Weather Company help the agriculture industry find value in weather insights. IBM Research collaborates with start up Hello Tractor to integrate The Weather Company data, remote sensing data (e.g., satellite), and IoT data from tractors. IBM also works with crop nutrition leader Yara to include hyperlocal weather forecasts in its digital platform for real-time recommendations, tailored to specific fields or crops. IBM acquired The Weather Company in 2016 and has since been helping clients better understand and mitigate the cost of weather on their businesses. The global expansion of Watson Decision Platform for Agriculture is the latest innovation in IBM’s efforts to make weather a more predictable business consideration. Also just announced, Weather Signals is a new AI-based tool that merges The Weather Company data with a company’s own operations data to reveal how minor fluctuations in weather affects business.

The combination of rich weather forecast data from The Weather Company and IBM’s AI and Cloud technologies is designed to provide a unique capability, which is being leveraged by agriculture, energy and utility companies, airlines, retailers and many others to make informed business decisions.

[1] The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”

[2] Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10


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What if Amazon used AI to take on factories?

By ANTONY BOURNE, IFS Global Industry Director for Manufacturing

Amazon recently announced record profits of $3.03bn, breaking its own record for the third consecutive time. However, Amazon appears to be at a crossroads as to where it heads next. Beyond pouring additional energy into Amazon Prime, many have wondered whether the company may decide to enter an entirely new sector such as manufacturing to drive future growth, after all, it seems a logical step for the company with its finger in so many pies.

At this point, it is unclear whether Amazon would truly ‘get its hands dirty’ by manufacturing its own products on a grand scale. But what if it did? It’s worth exploring this reality. What if Amazon did decide to move into manufacturing, a sector dominated by traditional firms and one that is yet to see an explosive tech rival enter? After all, many similarly positioned tech giants have stuck to providing data analytics services or consulting to these firms rather than genuinely engaging with and analysing manufacturing techniques directly.

If Amazon did factories

If Amazon decided to take a step into manufacturing, it is likely that they could use the Echo range as a template of what AI can achieve. In recent years,Amazon gained expertise on the way to designing its Echo home speaker range that features Alexa, an artificial intelligence and IoT-based digital assistant.Amazon could replicate a similar form with the deployment of AI and Industrial IoT (IIoT) to create an autonomously-run smart manufacturing plant. Such a plant could feature IIoT sensors to enable the machinery to be run remotely and self-aware; managing external inputs and outputs such as supply deliveries and the shipping of finished goods. Just-in-time logistics would remove the need for warehousing while other machines could be placed in charge of maintenance using AI and remote access. Through this, Amazon could radically reduce the need for human labour and interaction in manufacturing as the use of AI, IIoT and data analytics will leave only the human role for monitoring and strategic evaluation. Amazon has been using autonomous robots in their logistics and distribution centres since 2017. As demonstrated with the Echo range, this technology is available now, with the full capabilities of Blockchain and 5G soon to be realised and allowing an exponentially-increased amount of data to be received, processed and communicated.

Manufacturing with knowledge

Theorising what Amazon’s manufacturing debut would look like provides a stark learning opportunity for traditional manufacturers. After all, wheneverAmazon has entered the fray in other traditional industries such as retail and logistics, the sector has never remained the same again. The key takeaway for manufacturers is that now is the time to start leveraging the sort of technologies and approaches to data management that Amazon is already doing in its current operations. When thinking about how to implement AI and new technologies in existing environments, specific end-business goals and targets must be considered, or else the end result will fail to live up to the most optimistic of expectations. As with any target and goal, the more targeted your objectives, the more competitive and transformative your results. Once specific targets and deliverables have been considered, the resources and methods of implementation must also be considered. As Amazon did with early automation of their distribution and logistics centres, manufacturers need to implement change gradually and be focused on achieving small and incremental results that will generate wider momentum and the appetite to lead more expansive changes.

In implementing newer technologies, manufacturers need to bear in mind two fundamental aspects of implementation: software and hardware solutions. Enterprise Resource Planning (ERP) software, which is increasingly bolstered by AI, will enable manufacturers to leverage the data from connected IoT devices, sensors, and automated systems from the factory floor and the wider business. ERP software will be the key to making strategic decisions and executing routine operational tasks more efficiently. This will allow manufacturers to keep on top of trends and deliver real-time forecasting and spot any potential problems before they impact the wider business.

As for the hardware, stock management drones and sensor-embedded hardware will be the eyes through which manufacturers view the impact emerging technologies bring to their operations. Unlike manual stock audits and counting, drones with AI capabilities can monitor stock intelligently around production so that operations are not disrupted or halted. Manufacturers will be able to see what is working, what is going wrong, and where there is potential for further improvement and change.

Knowledge for manufacturing

For many traditional manufacturers, they may see Amazon as a looming threat, and smart-factory technologies such as AI and Robotic Process Automation (RPA) as a far off utopia. However, 2019 presents a perfect opportunity for manufacturers themselves to really determine how the tech giants and emerging technologies will affect the industry. Technologies such as AI and IoT are available today; and the full benefits of these technologies will only deepen as they are implemented alongside the maturing of other emerging technologies such as 5G and Blockchain in the next 3-5 years. Manufacturers need to analyse the needs which these technologies can address and produce a proper plan on how to gradually implement these technologies to address specific targets and deliverables. AI-based software and hardware solutions will fundamentally revolutionise manufacturing, yet for 2019, manufacturers just have to be willing to make the first steps in modernisation.

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