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Could the use of personal data decrease inequality?

Posted By Felistus Mbole, Tuesday, August 20, 2019

Felistus Mbole a member of our Emerging Fellows program inspects the role of personal data in decreasing inequality through her new blog post. The views expressed are those of the author and not necessarily those of the APF or its other members.

The one thing that defines the digital revolution we are in today is the enormous volume of personal data that is generated and collected each day. Data generation is growing at an exponential rate. This is supported by the ever-increasing computational power particularly in mobile devices. The use of smart devices is increasingly becoming part of our everyday lives. Through them, we are leaving a digital trail in almost everything we do. According to the Next Generation Data Analytics report, the big data market is expected to grow from USD 28 Billion in 2019 to USD 66 Billion by 2025. The trend is clearly upward. What does the continued generation and use of personal mean for economic inequality? Can the benefits of big data be made more inclusive?

The key drivers of the big data era are the growing number of mobile devices and related applications, and organisational shift from analogue to digital technologies. According to the World Bank, today more households in developing countries own a mobile phone than have access to clean water or electricity. Furthermore, close to 70 percent of the bottom wealth quintile in these countries own mobile phones. Businesses and governments are becoming smarter each day. They are developing algorithms which enable them to analyse big data and make predictions with a much greater level of precision than would be the case with huge national surveys. This is making decision-making easier.

Governments now have access to a mass of large-scale data sets, and new data sources on previously ‘unknown’ populations. They are using big data to cost-effectively make predictions that enable them to provide better services to their citizens. For instance, healthcare professionals can use big data to calculate someone’s chance of suffering from a given disease and thus provide timely or preventive treatment. Big data has been used to increase financial inclusion, improve education, respond to epidemics, and mitigate the impact of natural disasters. Businesses on the other hand are using data freely collected from individuals to provide services and products that are more targeted at their clients. Using algorithms, they can more accurately anticipate behaviour. They are driving our future behaviour. This form of surveillance capitalism is making data companies much more profitable and driving the inequality between them and the rest of society.

The role of technology companies in making connectivity work for everyone in future is likely to remain. Yet the reality is that business decisions on investments are driven by the need to optimise returns. Thus, despite the dividends highlighted here, a digital divide between the rich and the poorer in society who cannot afford the latest technology is likely to persist. The poor and the digitally excluded have less or incomplete data which makes them excluded from services whose design is informed by machine learning. Additionally, the algorithms can be discriminative and biased. For instance, health insurance services algorithms use historical data which could have biases. Credit scoring algorithms use residential location and type of work which could further entrench one’s economic situation. These could sustain the prevailing global inequalities.

The economy of the future will be digital. Based on the current trajectory, big data and machine learning is likely to increase. As the revolution of big data and artificial intelligence takes root, there will be loss of jobs. The poor in society who do not have the requisite digital skills to engage in this big data economy are likely to be disadvantaged and excluded economically. This could increase global inequality. The digital divide between the richer and the poor could be closed by addressing the non-digital or analogue elements behind it. Adapting the skills of workers to the digital economy, the nationalisation of data, and effective regulation of business to ensure digital inclusion would help address this digitally driven inequality.

© Felistus Mbole, 2019

Tags:  data  inequality  technology 

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In a digital economy will the abundance of data fuel a golden age of wisdom?

Posted By Paul Tero, Thursday, June 6, 2019

Paul Tero a member of our Emerging Fellows program examines the possibility of building an age of wisdom in the digital economy. The views expressed are those of the author and not necessarily those of the APF or its other members.

 

Knowledge in action. Sagacity. Percipience. Having experience, knowledge and good judgement. These words and phrases all describe and define wisdom. But will an abundance of data lead us to a golden age of wisdom? Will a richness of facts and figures, statistics and evidence lead us to a never-ending harvest of good judgement?

 

If we give credence to the DIKW (data, information, knowledge, wisdom) information science hierarchy, the answer leans to the affirmative. For with this framework, the following is the pattern: firstly, an abundance of data certainly leads to a wealth of information, or descriptions, about a plethora of matters. Which should, in turn, facilitate a breadth and depth of knowledge that is available for teaching and mentoring at a level unsurpassed in human history. Where the fruits of expertise, of mastery and of prowess collectively form this knowledge. And where this teaching and mentoring is an enabler to all people across the world regardless of the strata of society in which they sit. Where all of this upward flow of data, information and knowledge leads, finally, to a culmination in a golden age of wisdom. A time of good judgement and wise action.

 

But is the preceding flow true if we use a different time horizon? This piece you are reading is written for a timeframe of several decades into the future. What if you and I were to wind the clock back several decades to a time where “today was that tomorrow of several decades into the future”? Comparing this “back-in-time today” to the “current-time today”, is the latter enriched with an abundance of data? Do we, in the “current-time today” have a wealth of information about a plethora of matters compared with the times past. And thirdly, with respect to the current times, do we not have the ability, through information and communications technology, to teach and to share the fruits of expertise globally?

 

The argument can be made that we are better off today than yesterday. That we are wiser, that we have made sound judgements. While there is so much more to do, we can point to improvements in economic and physical health across the globe. We can make mention of the reduced rates of nation-state armed conflict and of improvements in education. But as we cast our eyes forward, will the teenage grandchildren of today’s teenagers be enveloped in, and benefit from, a milieu of experience, knowledge and good judgement? Consider the following two scenarios.

 

While matters of family are a common thread, that young woman in Asia, on the cusp of adulthood, may well have a personalised AI avatar to guide her through career and social choices. Offering her advice that could be heeded. And what-about that young man? A product of his Western heritage, looking to develop a career in the physical trades, finding his options don’t include the routine work he desires. Just like he was told throughout his schooling years.

 

In both cases, wisdom is offered but not infused. The prospects are that tomorrow will be just like today. Today we have that abundance of knowledge and the capacity for wise outcomes. And tomorrow? Our knowledge will have grown, we’ll have intelligence on hand and our capacity for delivering wise outcomes will be enhanced, but whether or not our results reflect these well-developed inputs is surely debatable.

 

These same arguments can be made regarding the generation of these teenager’s parents. Regardless of whether they live in Africa, the Sub-continent or in the Global North, one can imagine these parental pillars of society having responsibility in business or in policy making. Where the leaders in business are bound to a then long-established fiduciary duty to consult digital oracles. Where the policy makers can freely receive a finely curated harvest of good judgement.

 

Again it plays out in these two cases, decisions not quite fully imbued with the wisdom on offer. For across all four of these vignettes witness a surfeit of data, of information and of knowledge ripe with judicious potential. But where the consumption of this particular fruit is not universal. And the common denominator? What stands in front of this golden age of wisdom is surely our inherent human nature.

 

© Paul Tero 2019

Tags:  data  economics  wisdom 

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