The Effects of Machine Learning

The Effects of Machine Learning

The Effects of Machine Learning

Machine learning, also known as Analytics 3.0, is the latest development in the field of data analytics. Machine learning allows computers  to take in large amounts of data, process it, and teach themselves new skills using that input. It’s a way to achieve artificial intelligence, or AI, using a “learn by doing” process.

Machine learning enables computers to learn and act without being explicitly programmed. It evolves from the study of pattern recognition and the design and analysis of algorithms to enable learning from data and make possible data-driven predictions or decisions. It is so pervasive today that many of us likely use it several times a day without even knowing it.

In earlier stages of analytics development, the companies that most benefited from the new field were the information firms and online companies that saw and seized the opportunities of big data before others. The ability to provide much needed data and information represented  a clear first mover’s advantage for these companies. While the first movers in big data were the big winners, their advantage won’t last much longer as productivity levels out. The evolution to Analytics 3.0 is a game changer because the range of business problems that intelligent automation — a mixture of AI and machine learning — can solve is increasing every day. At this stage, nearly every firm in any industry can profit from intelligent automation. Companies that invest immediately in machine learning have the potential to gain long-term benefits, profiting from the work of analytics pioneers. To gain these benefits, companies must rethink how the analysis of data can create value for them in the context of Analytics 3.0.

Beneficial Applications Versus Risks of Machine

Key Considerations and Implications

  • The moral component — The level of intelligence and “morality” that a machine exerts is a direct result of the data it receives. One consequence is that, based on the data input, machines may train themselves to work against the interest of some humans or be biased. Failure to erase bias from a machine algorithm may produce results that are not in line with the moral standards of society. Yet not all researchers, scientists and experts believe that AI will be hurtful to society. Some believe that AI can be developed to mirror the human brain and obtain human moralistic psychology to enhance society.
  • Accuracy of risk assessments — Risk assessments are used in many areas of society to evaluate and measure the potential risks that may be involved in specific scenarios. The increasing popularity of using AI risk assessments to make important decisions on behalf of people is a direct result of the growing trust between humans and machines. However, there are serious implications to note when using a machine learning system to make risk assessments. A quantitative analyst estimates that some machine learning strategies may fail up to 90 percent when tested in a real-life setting. The reason is that while algorithms used in machine learning are based on an almost infinite amount of items, much of this data is very similar. For these machines, finding a pattern would be easy, but finding  a pattern that will fit every real-life scenario would be difficult.
  • Transparency of algorithms — Supporters of creating transparency in AI advocate for the creation of a shared and regulated database that is not in possession of any one entity that has the power to manipulate the data; however, there are many reasons why corporations are not encouraging this. While transparency may be the solution to creating trust between users and machines, not all users of machine learning see a benefit there.

Next, we highlight some of the ways these implications play out in several industries.

Spotlight: Industry Implications

Today, artificial intelligence makes it possible to predict the likelihood of a heart attack with much better accuracy than before. While manual systems are able to make correct predictions with around 30 percent accuracy, a machine learning algorithm created at Carnegie Mellon University was able to raise the prediction accuracy to 80 percent. In   a hospital, an 80 percent prediction theoretically would give a physician four hours to intervene before the occurrence of the life-threatening event.

However, the accuracy of risk assessments in the medical field may vary depending on the level of bias in the research used to train the machine learning algorithm. For instance, most heart disease research is conducted on men, even though heart attack symptoms between men and women differ in some important ways. If the system is trained to recognize heart attack symptoms found in men, the accuracy of predicting a heart attack in women diminishes and may result in a fatality. For that reason, people who are affected by decisions based on AI risk assessments will want to know how these decisions are systematically made.

Hedge funds, which have always relied heavily on computers to find trends in financial data, are increasingly moving toward machine learning. Their goal is to be able to automatically recognize changes in the market and react quickly in ways quant models cannot. Most of these algorithms are proprietary, for a reason. The risk of having transparency in this case is that as one fund becomes successful using a certain algorithm, others will want to mimic that company’s machine learning method, diminishing everyone’s success and creating an artificial market environment. For this reason, any regulation that attempts to control the transparency of AI must be suitable and appropriate to the various scenarios where AI is used.

The U.S. National Highway Traffic Safety Administration recently released guidelines for autonomous vehicles, requiring auto manufacturers to voluntarily submit their design, development, testing and deployment plans before going to market with their vehicles. Despite these efforts to increase the transparency around “the brains” deployed in autonomous vehicles, car manufacturers, tech companies and auto parts makers are in a tight competition to develop the software behind self-driving cars, and their need to keep development efforts under wraps to gain market advantage may end up hurting the future of autonomy.

In addition, the nature of machine learning itself makes it very difficult to prove that autonomous vehicles will operate safely. Traditional computer coding is written to meet safety requirements and then tested to verify if it was successful; however, machine learning allows a computer to learn and perform at its own pace and level of complexity. The more automakers are willing to be transparent about the data they input into the learning algorithms, the easier it will be for lawmakers and auto safety regulators to create laws that will ensure the safety of consumers.

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Nigeria, with the largest population, economy and consumer market in a rising Africa, shows great market opportunities for those that wish to tap into Africa’s imminent boom in consumer spending. The country is expected to have the world’s second fastest-growing middle class, which are to reach 15 million households in 2030, and with the young urban population Nigeria provides a vibrant telecom scene. The number of smartphone users is expected to increase to 35 million by 2017. The Nigerian economy showed strong growth up on till 2015, when the growth slowed down due to the effects of the fall in the global price of crude oil, leading the authorities to adopt an expansionary 2016 budget with the aim to stimulate the economy. This has affected the hardware and mobile sales, the two main drivers of growth in the ICT sector, as it has decreased both the population, corporate and the governmental purchase power. Regulatory figures indicates that the mobile sector contracted by 1.5 % in the first quarter of 2016 and the hardware segment with 29.5 % in US dollar terms in 2015. Even though the mobile sector contracted, the mobile app usage is currently growing at an exponential rate and the ICT in general still holds 8.5 % of the national GDP. Even though the outlook for 2016 is a slow recovery of the ICT market, BMI forecasts
suggest that 22% of the Nigerian households, a number that will increase to 34% in 2020, have an annual income sufficient to have the purchasing power for imported computer hardware. A strong governmental aim in combination with initiatives from private investors suggests that broadband internet connections will rise steadily, from an estimated 15.49 million at the end of 2015 to a forecast of 38.79 million at the end of 2020. Key growth factors of the mobile segment such as rapid network expansion to underserved areas, promotional offers, economic growth, rising income levels and future subscriber growth opportunities shows potential for resumed growth, although caution is advised as the immature IT marker is vulnerable to the volatility of the Naira.


Nigeria’s consumer market, with its great potential, has attracted significant investment both from private and public sectors in a wide range of industries. One example of this are local and international retailers such as SPAR and Shoprite who has announced plans to open ‘hundreds’ of stores across Nigeria within the next few years. This will exercise pressure for modernization in order to spur the adoption of solutions for effective customer management and efficient service to gain competitive advantages. Parallel with this there is an ongoing development towards increased e-commerce as network infrastructure is improved. With 300,000 online orders being made on daily basis Nigeria’s ecommerce market is valued at around 10 billion USD a year. This increase in e-commerce will be an important demand driver for IT solutions such as transaction processing and online security systems. Financial services, retail, and aviation sectors are therefor expected to ramp up their IT investments to remain competitive.
This development is very much aligned with the governments’ strong will to develop e-services, which constitute opportunities for foreign players since there is deficiency of skilled domestic workforce in these areas. These services include e-government, cloud computing, e-healthcare, e-learning, eagriculture, e-education, e-commerce, m-payment and services in charge of fighting cybercrime. There is also a growing demand for mobile enabled high-definition video, gaming services and internet based television in the middle-class market segment. Whereas the country may lack domestic skills in the development of e-services, the production of end user devices has remained stable with five PC assembly plants in Nigeria and a total production of 130,000 units, which indicates that 30% of all PCs sold in Nigeria are assembled in the country.
The Nigerian government is spurring the development of a stronger ICT sector by, for example, providing tax incentives and seed capital to ICT startups, a 120% tax deduction for R/D expenses incurred by ICT training companies and 5 years import duty waiver on computer components used for assembly of hardware. Apart from the government’s willingness to invest, there is also an expected increase of IT spending in Nigeria’s telecom sector. The telecom sector has shown strong subscriptions and value growth since the liberalisation of the market in 1999 and telecoms operators are presently the biggest users of BPO services in Nigeria.


There are a number of infrastructure development projects ongoing in Nigeria aimed to further the implementation of national broadband deployment and increase of internet access. Five undersea cable systems with more than 100 000 km of terrestrial fibre-optic cable, connecting Nigeria to Europe and the US boosted data capacity to over 12Tbps. The Nigerian Communications Commission has also granted Infrastructure Company licences for two operators in the Lagos region and the North Central Zone as well as announcing plans to allocate the five remaining licences during 2016. This will drive investment in high capacity fibre optic networks throughout both regions. Broadband internet subscribers currently make up over 79% of the internet population.
With Kenya and Ghana as role models Nigeria need to strengthen its domestic political institutions as well as to implement a coherent ICT policy umbrella in order for the ICT sector to really take off. The potential for cloud computing is however promising as network infrastructure improves. A number of the biggest telecom service providers have invested in metro fibre networks in key business districts of Lagos and Abuja and launched 3 datacentre in Lagos to provide necessary infrastructure for cloud based IT services. Inaction on product counterfeiting is highly problematic on the Nigerian hardware and software market and will continue to undermine the growth, with the greater prospect for reduction arising from cloud service provision rather than action by the government.


The retrenchment in consumption as a consequence of the steep naira depreciation has hit the immature IT market hard, as it is mainly dominated by the hardware segment. Even though the Nigerian ICT market means high risk and unlikelihood to provide short-term rewards its sheer size presents long-term opportunities too good to resist. Vendors are willing to invest in order to position themselves for future growth and despite the current market volatility there are specific opportunities in Nigeria over the medium term, for instance in the expanding premium hardware market and enterprise sales in a few key verticals.
Mobile commerce is gradually taking off in Nigeria, though rather slowly. Key telecom service providers in Nigeria have however formed partnerships with financial institutions to comply with the Central Bank of Nigeria’s framework for m-commerce services, suggesting there are greater investments to expect in this area. Telecom infrastructure development in some parts of the country remains inadequate and as growth in urban areas falls, the rural markets is expected to be the next frontier, increasing the m-commerce potential even more as the access to cash in these areas are very limited.
With the rapid expansion of the IT sector and increased demand for security systems in combination with a number of sectors expecting to ramp up their IT investments, interesting investment opportunities for foreign companies are to be find in infrastructures and internet access providing, engineering services, software and content development, M-commerce, E-government, training and ICT related services. There are also some opportunities for companies in far stretched relations with the IT sector, for example, providers of surrogates to fossil fuels. Even though the prices of petrol and diesel has decreased the pressure on finding other power solutions remain high when telecom operators spend an estimated 288 million USD to purchase diesel for the 20,000 generators located in over 15,000 sites in Nigeria.


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