How Data for Good Can Be Used to Improve Our World

Data for good

Data for good (Pexels)

Using data for good is critical for the future of humanity – and organisations will be pressured to halt bad practices sooner rather than later

I’m determined to promote data for good. Why? As an inherently on-demand generation, we constantly hear about the data imperative: the continual rise in our rate of data consumption. By 2025, it’s estimated that some 463 exabytes of data will be created globally every single day. And there many ways in which this data is collected (sensors, Internet of Things), stored (private, public and hybrid cloud), analysed (artificial intelligence, machine learning) and monitored (dashboard, feeds) with increasingly real-time reporting on the insights gained. 

Much attention is given to the technology – its integrity, availability, traceability and security, as well as the human right to privacy. But there is increasing awareness, too, around the value of data, now frequently cited as the new ‘oil’ of industry

Often we hear stories and see headlines about data “gone bad” – incidents of accident or abuse where data is maliciously accessed, collected without consent, stolen or faked. This primarily takes place through inadequate data protection in the enterprise, malevolent use of data aggregation and data mining techniques and lack of user awareness of the risks. It results in behaviours that increase individual vulnerability, and shape broader societal fears around data sharing. But this fear does not simply stem from the latest development in AI or automation; it’s always been there. 

Taking voice as an example, before Alexa and privacy scares, we saw a similar level of concern in relation to the Apple iPhone tracking its users. And most recently it has again manifested in concerns around temporary ‘symptom tracker’ mobile applications that have emerged in the fight against COVID-19. 

Connecting The Data Dots

What connects them is the perception of lack of control and/or awareness on how to manage privacy and security, coupled with a lack of knowing or trusting how data will be used, stored or shared with others, especially in the context of sensitive personal data. 

These are concerns that can be negated by improving awareness and transparency around ePrivacy and GDPR compliance, embedding trust within the technology through modern data protection and establishing structures that facilitate the use of data for the “common good”. It can also be greatly supported by demonstrating real-world, secure examples of data applied for social impact. It’s time to change the narrative. It’s time to use data for good. 

We can be informed by data and enlightened by the numbers and nuances that arise from its analysis – but equally, we can also be driven by principle in the ways this value is applied. 

While data has the power to transform business, government and even entire industries, it can catalyse and scale societal transformation too. This is the very ethos of data for good, powered by shared-values leadership, cultural readiness and investment in holistic skills development – and in partnership with the application of emergent technologies, notably big data analytics, AI, automation and machine learning. 

Developed ethically and used appropriately and responsibly, technology and the data that results can help uncover new opportunities and expediently solve complex problems. 

Man And Machine

This combination of talent and technology can be shared with a broad range of organisations including charities and social enterprises allowing deeper insights into data – and actions from this understanding – than would otherwise be available. 

This is illustrated by IBM’s Science for Social Good program with the charity St John’s Bread & Life. It is a great example of what can be achieved through partnership. Providing food and social services in New York, the infusion of expertise and technology tools enables better analysis of the organization’s data and an enhanced understanding of its food supply chain and performance. This has allowed the charity to optimise its resources and focus on serving the people who need their life-changing services. 

And when talent, technology and collaboration come together, incredible advances can be achieved, as exemplified by the solidarity of the technology sector in the fight against COVID-19. A notable example is the rapid establishment of the HPC Consortium involving IBM and 10 other leading tech firms to support federal government, industry and academic leaders across the world with access to expertise and high-performance computing capacity to help accelerate the research curve in combating the disease. 

With a mobilisation such as this, it is no surprise that by early April 50 potential vaccines and nearly 100 possible treatment drugs were in development. 

New Opportunities

The data for good application opportunity is as significant as it is diverse. While location data can help us better prepare for and recover from natural disasters, negate the spread of disease and protect the environment via enhanced monitoring, so historical data can enable organisations to better understand past behaviours to predict future trends. And in many cases how we apply data can be highly pragmatic and significantly evolve.

Take, for example, Google’s use of data to predict the prevalence of flu in 2008 based upon terms people were searching. Irrespective of the flaws of this approach this was early recognition of how data can be reused to offer fresh insights into issues which were never in the scope of original use.

Data repurposing and technology adaption also opens the door to new opportunities for addressing age-old problems such as air pollution – which has been an issue since the days of ancient Rome – or relatively new issues like waste plastic with debris first observed in our oceans during the 1960s. And this does not need to be wholly driven by traditional data science experts but can be more openly supported with research at least partly conducted by citizen scientists – members of the public. As an example, the integration of community and technology (mobile app, web portal and public database) to launch Marine Litter Watch is supporting both cleanup and monitoring events on beaches and other stretches of coast. 

Archived data can also achieve new life. In fact, this remains one of the greatest latent and under-recognised business and societal assets of our time – and moreover, one of the biggest wastes; a digital variant of the plastic waste crisis. Let’s harness this data for good. 

Data For Good – For The Future

Despite the veracity, velocity and volume of data we continually create and consume, around 90 per cent of digital data is not used and 90 per cent of data is never accessed again – just three months after it is first stored. 

Opportunities for data reuse transverse digital transformation for business to societal transformation for us all. When we think of the digital equity gap, we primarily focus on unequal access to the internet. And while this remains a global imperative, there are other areas of inequality too, going beyond devices and infrastructure, to the training of teachers on how to best to incorporate technology to enable a consistently high learning experience. 

This requires access to data sets to help best train the talent of the future – and equally upskill or reskill those already within the world of work.  And to apply this data for good and at scale, the data itself needs to be good, of sufficient volume, accessible and secure. 

This is where the developing partnership between Aspirational Futures and IBM Systems Europe comes to the fore, forming a bridge across education and technology to democratise access to equal opportunity, breaking down the digital equity gaps. One immediate area of focus is addressing the growing talent and inclusion gaps in the technology industry. Taking cybersecurity as just one example, recent research identifies 2.8 million professionals working in this area worldwide – but also that an additional four million trained workers are needed. 

Related to this are broader skills shortages especially around STEM competencies alongside a lack of diversity in who is studying and ultimately working in these fields, with under-representation notably affecting women but also effecting a greater range of characteristics. Further, this partnership recognises that careers are fluid and people increasingly work across different sectors and need holistic skills to navigate and moreover embrace this way of working. The so-called ‘soft skills’ are pivotal here and we are also supporting a depth and breadth of training packages to include vital competencies in effective communication, critical thinking and problem solving, empathy and emotional intelligence. 

In conclusion, data for good is a movement and an ethos in which people and organisations transcend individual, professional and organisational boundaries to use data to improve society. If we come together, we can combine digital transformation for good business with digital compassion and democratised access to opportunity for all.

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