Connecting the present and the past, learning and drawing conclusions from either, is and will remain key to creating a more sustainable fashion industry. So far, learning from the past in particular - in the good and in the bad - has been chiefly neglected. A series of thoughts.
Digital tools and IT systems are a great enabler for more data, more stringent channels of how to communicate what the different players in the chain do, and how they do it, over large distances and across operations and organizations.Yet – digital tools are more human than we think they are … because they, in the end, are representatives of the values and the world view of those that have built them.
Could ESG reporting finally become less repetitive and tedious?
AI has the potential to transform ESG reporting by automating compliance tracking, integrating data from diverse and unstructured sources, and streamlining audit preparation. This opens up opportunities to free data and ESG experts from repetitive, tedious tasks. Yet, while AI offers promise, tight oversight remains essential to address challenges like data quality ('crap in is crap out') and system integration.
AI has the potential to transform corporate responsibility by handling data-heavy tasks like reporting or data and KPI management. It hence can contribute to helping companies 'being less bad'. However, its potential to support professionals and companies in driving real positive impact is still developing. This post introduces AI’s current potenntial in corporate responsibility and sustainability. In upcoming blog posts we'll explore specific applications: in sustainability reporting, supply chain management, and integrating financial considerations with sustainability impact.
The term ‘circular economy’ has recently been – again – converted into a buzz word. To some extent there are a couple of good reasons for that as both common sense as well as the Ellen McArthur foundation's most recent report prove.
At Shirahime, we have worked quite extensively over the last few months on the development of fashion industry scenarios beyond the 2020 time frame, going as far as 2045.
We mentioned for example Shell as one that used this approach to suit their own goals.
Siemens' 'Future Life' video, as presented the The Crystal in London.
A much more interesting approach, and very insightful in terms of methodology, but also how tangible the results are presented, is Siemens’ work on Future Cities
The most recent event in the 'Perspectives on Future Sustainable Design' series highlighted the progress made in developing sustainable design approaches. Both, from a theoretical as well as from a systemic point of view. A summary.
Can AI help us to get to (better) grips with supply chain compliance?
Supply chains are based on fairly complex partnership networks where every link ideally must meet strict efficiency and compliance standards.
Supplier audits and legislation aim ultimately to ensure high standard, it is a not the least highly time demanding task to be successful at. AI offers the potential to support practical solutions for risk assessment, process optimization, and partner evaluation. Commercial providers are already jumping on the band wagon by providing ways to build 'digital twins' of real supply chains – hence opening them up for 'offline optimisation' - and of course highly sophisticated data analytics tools drawing from multiple disjoint data sources.
Supply chains, as a discipline of expertise, have come out of the hiding and recognise their role in reducing corporate risk. This is notably and specifically the case in fashion and textiles. At the same time, 'design' - not just in the creation room, but in all facets where it impacts the making, delivery and use of a product or service, is increasingly recognised as relevant.
Cotton as an attractive alternative in tsunami regions. Leading textile manufacturers promoting the cultivation of organic cotton. New technologies and methods for natural dyeing processes and recycling. And five categories of Green Fashion in Japan.
How does digitalisation impact and link to corporate responsibility? This is the question we look into in this post.
Combining the two disciplines results in a range of interesting questions. For example: If humans create non-human agents (e.g. in the shape of AI): For what, towards whom are these responsible? And: are they responsible at all - or is it their creator who is?
Overconsumption or ‘simply’ consumption?
Fair resource use, or resource depletion?
Fair share, equal share or acquired share of resources?
Those are questions that pop up when the Planetary Boundaries are being discussed.
“Is Europe living within the limits of our planet?: An assessment of Europe's environmental footprints in relation to planetary boundaries”, published in April 2020 does exactly that: it evaluates and calculates the European performance for planetary boundaries by taking a consumption-based (footprint-based) perspective. This is turn is interesting as it relates environmental pressures to final demands for goods and services.
And the results are ... shall we say: a stark call to action.
The RITE Conference's 2012 edition showed that the challenges for the industry are clear, and so are the general directions that need to be taken. But there are some marvellous and challenging mountains to climb, and they cause a notably sensation of paralysis.
Japan – for multiple reasons, not the least the still ongoing, if diminishing, cultural influence onto its neighbours – remains an interesting case to look at in terms of sustainable and ethical fashion. And vocabulary and its use and evolution is the start of it all.
After 10 years in the make, CETI, the European Centre for Innovative Textiles, was finally inaugurated in October 2012. The aim of the research centre is to give the textile industry a platform to research and prototype innovative textiles that can be used in sectors like: Medical, Sport & Leisure, Hygiene, and Protection sectors representing 25% of technical textile manufacturing industry; building and civil engineering that account for 10% of the production; transport making 26% of the market volume (and 15% of the market value) of technical textiles.
Have you heard about open data? And about open source?
The equivalent of open source in sustainability terms would be an ‘open standard’.
But what would that mean?
Is AI advancing sustainability or creating costly trade-offs we’re only beginning to understand? In this post, we dive into the reality behind AI's potential as a force for sustainability. While AI shows promise in enhancing sustainable practices and supporting business processes, it also has a significant CO₂ footprint—mainly from energy-hungry data centres—and its environmental impact will likely grow. Though AI could help achieve Sustainable Development Goals, this depends on our responsible use and governance of the technology. Without stringent oversight, AI risks reinforcing societal biases, as seen in social media algorithms that foster echo chambers. As with all innovations, AI’s promise is matched by its challenges, and only a well-balanced approach can ensure it contributes meaningfully to a sustainable future.
The fashion industry, nearly like no other, has gone through dramatic changes in the last 20, 30 years. Indeed it finds itself in the present at a crossroad. Resource scarcity is triggering shifts in business models and supply-chains; waste is the new resource; customers are the sales channel of the future; and legislation is becoming ever more stringent. The fact though is: if looking back at predictions of the 1950 and 1960, or even earlier (physical artefacts not considered), the reality we live in compares best to the predictions that were considered ‘totally crazy’ in their time.
How can AI help connect the worlds of sustainability/ESG data, and that of company financials?
ESG is typically considered a mere cost - yet: this perception stems chiefly from a lack of integration of mutually beneficial data of these two worlds. With better approaches to cost accounting, to performance analysis, as well as using predictive analysis relate to trends, legislation and asset management, the ability of AI to integrated diverse and complex data sets may precise be the pathway to shift that needle.
Computer Science and Sustainability/ESG: these two areas of expertise combine increasingly well with every passing month and year. In fact, I am tempted to say that the two worlds of sustainability and digitalisation are surprisingly similar to one another. In a number of ways – not in all, of course! – they overlap more than they differ. And mutually benefit each other.
Both areas represent critical skill-sets for boards and senior executives in the current and upcoming decades. This is why I thought I’d take the time to reflect on the overlaps, the synergies, but no doubt also the differences.
The key words: systems thinking, automatisation, fraud prevention and authentication, business model distruption, usability, and the Just Transition.
