Artificial Intelligence For Fantastic – Also Makes Business enterprise Sense
augmented intelligence certification (AI) has been put forward as a potential solution for many of the gravest problems facing society, from the opioid crisis to poverty and famine. </p><figure class="image-embed embed-0" role="presentation"><div><img src="https://specials-images.forbesimg.com/imageserve/5d36f26195e0230008f64c58/960×0.jpg?cropX1=624&cropX2=5616&cropY1=351&cropY2=3159" alt="augmented intelligence certification For Good – Also Makes Business Sense" data-height="3511" data-width="6241"></div><figcaption><fbs-accordion><p class="color-body light-text">augmented intelligence certification For Good – Also Makes Business Sense</p><small>Adobe Stock</small></fbs-accordion></figcaption></figure><p>But although technology clearly has the potential to do a great deal of good, there’s a sound business reason that tech companies often pour large amounts of resources into social projects that don’t seem to align with their core business of selling software and services. </p><p>This is down to the fact that tackling social issues often involves developing solutions to problems very similar to those faced by businesses. Additionally, working with governments or NGOs on building these solutions can often mean access to new datasets. Learning derived from these datasets can later be developed into products and services to offer to clients (even if the data itself isn’t).</p><p>In 2016, IBM launched a program of initiatives called Science for Social Good. It aimed to develop technology-driven solutions to 17 issues highlighted by the United Nations as <a href="https://sustainabledevelopment.un.org/?menu=1300" target="_blank" class="color-link">Sustainable Development Goals</a> (SDGs). These include reducing poverty, inequality, and damage to the environment, as well as raising standards of healthcare and education across the world.</p><p>Today IBM has announced progress that has been made across 15 of those 17 initiatives thanks to technology and research it has carried out. I got the chance to speak to two people involved with this work – IBM fellow Aleksandra Mojsilovic and principal researcher Kush Varshney – about why this work is valuable to IBM itself, as well as society as a whole. </p><div class="vestpocket" vest-pocket></div><p>Mojsilovic told me “Around 2013 or 2014, we were trying to figure out a way to do something good with our skills and one of the emerging things back then was the Ebola epidemic – we thought that putting our data skills to work to help with that would be fantastic and we learned a lot of lessons from doing so. </p><p>"But we found that people were mainly ‘doing good’ as a volunteer effort – weekends and hackathons, that sort of thing, which didn’t quite seem right. IBM research is pretty big, we have over 3,000 researchers around the world, and we decided there had to be a way to leverage these skills more broadly and in a coherent way … it didn’t really seem right that we were just trying to solve these problems in our spare time."</p><p>This was where the idea of integrating IBM’s Science for Social Good with the UN’s SDG’s first emerged, and its researchers realized the importance of collaborating with governmental and NGOs with expertise in their fields. </p><p>“One thing we learned from Ebola was that we were a bit arrogant,” explains Mojsilovic. “We thought we have all these skills which we can use to do a great deal of good; then we got a wake-up call because we realized that these incredibly difficult problems have components to them, and some are solved by truly understanding the problem, and others by truly understanding the technology. </p><p>“We learned that having a program that’s really focused on creating tools or technology won’t work without the participation of those who really work with these problems."</p><p>Several initiatives were developed that tied directly into the UNs SDGs. These included one that aimed at fairness around risk assessment in financial services, including health insurance in the US and mobile-based money lending programs in east Africa. Here, the aim was to use technology to mitigate against the risk of bias leading to unfair or discriminatory outcomes. </p><p>Another aimed the opioid epidemic currently plaguing the US, by harnessing machine learning to determine which patients were more likely to become addicts after being prescribed opioid treatments.</p><p>Other initiatives include driving data-driven research into multiple sclerosis, developing AI-driven systems to assist those on low incomes with managing their finances, assisting the UN in driving its sustainable development goals and predict outbreaks of Zika virus. </p><p>As well as knowing that they were helping to solve some of the most difficult scientific problems facing our species and planet, researchers were spurred on by the fact that their work also has value for IBM and their clients. </p><p>Mojsilovic tells me, "For example … the opioid project involves causal modeling – a really hot topic right now in machine learning. </p><p>"So when we started looking at problems where causal modeling could help, many of them are in this space of social intervention, policy development, healthcare intervention, genomics – so now you get phenomenal material to try out your techniques, and the big problems feedback to inform you … you create a library of reusable assets, which you can apply to so many problems."</p><p>Working on world-scale social problems also helps IBM and other tech companies to investigate ways of scaling their solutions to fit world-scale business problems.</p><p>One example of how this is already being used to help IBM clients is the AI Fairness 360 platform. Elements of this were developed thanks to the work on improving social inclusion and fairness in finance and lending, Varshney tells me. </p><p>“Fairness is a big topic right now in machine learning research. Several projects in the Science for Good program are around fairness … gender equality or other forms of equality, and working on fairness in those settings help us to move forward on this journey. Then it’s about pulling it all together to create these core technologies … and putting some of those capabilities into the IBM product.”</p><p> So, while it’s still true that virtue can be its own reward – helping to tackle world problems at UN-scale as part of their day-to-day work is likely to increase job satisfaction – there are certainly sound business reasons behind IBM (and others’) decision to dedicate resources to solving the world’s problems. </p><p>As Varshnay tells me, “We’re also very aware these are huge problems, not the kind of things we will solve with a project or two – they are going to take decades to solve.</p><p>“We’re building blocks that others can use and re-use, and take them further – it would be arrogant of us to say we’re here to save the world, don’t want the message to come across like that!” </p>”>
augmented intelligence certification (AI) has been put forward as a opportunity resolution for many of the gravest difficulties experiencing culture, from the opioid crisis to poverty and famine.
But although technological know-how obviously has the opportunity to do a terrific offer of fantastic, there is a seem small business motive that tech providers usually pour massive quantities of assets into social initiatives that don’t seem to be to align with their main small business of marketing software and providers.
This is down to the fact that tackling social problems typically includes building alternatives to problems really related to people faced by firms. Furthermore, working with governments or NGOs on developing these solutions can generally mean access to new datasets. Studying derived from these datasets can later on be made into solutions and solutions to offer to customers (even if the facts alone is just not).
In 2016, IBM released a plan of initiatives termed Science for Social Good. It aimed to acquire technological innovation-driven answers to 17 troubles highlighted by the United Nations as Sustainable Enhancement Goals (SDGs). These include decreasing poverty, inequality, and problems to the setting, as nicely as raising criteria of healthcare and education throughout the planet.
Nowadays IBM has introduced progress that has been designed throughout 15 of individuals 17 initiatives many thanks to engineering and study it has carried out. I acquired the probability to communicate to two folks included with this get the job done – IBM fellow Aleksandra Mojsilovic and principal researcher Kush Varshney – about why this do the job is valuable to IBM by itself, as perfectly as society as a complete.
Mojsilovic told me “Around 2013 or 2014, we were being attempting to figure out a way to do a little something superior with our skills and one particular of the rising points again then was the Ebola epidemic – we imagined that putting our data skills to perform to help with that would be wonderful and we learned a whole lot of classes from carrying out so.
“But we discovered that people today were being generally ‘doing good’ as a volunteer exertion – weekends and hackathons, that form of matter, which didn’t rather feel suitable. IBM investigate is very significant, we have more than 3,000 scientists all over the earth, and we made a decision there experienced to be a way to leverage these skills additional broadly and in a coherent way … it didn’t seriously appear to be suitable that we were being just attempting to clear up these difficulties in our spare time.”
This was where the concept of integrating IBM’s Science for Social Very good with the UN’s SDG’s to start with emerged, and its researchers recognized the worth of collaborating with governmental and NGOs with expertise in their fields.
“One factor we figured out from Ebola was that we were being a bit arrogant,” points out Mojsilovic. “We considered we have all these skills which we can use to do a great deal of superior then we obtained a wake-up contact mainly because we recognized that these unbelievably challenging challenges have parts to them, and some are solved by really knowing the difficulty, and other folks by truly knowledge the know-how.
“We realized that possessing a software that is definitely targeted on generating tools or technologies is not going to function devoid of the participation of these who actually work with these issues.”
Several initiatives had been developed that tied immediately into the UNs SDGs. These included one particular that aimed at fairness around possibility evaluation in fiscal services, which includes overall health coverage in the US and mobile-based funds lending systems in east Africa. Listed here, the goal was to use technology to mitigate towards the threat of bias top to unfair or discriminatory results.
A different aimed the opioid epidemic currently plaguing the US, by harnessing machine learning to determine which patients were much more likely to grow to be addicts right after currently being recommended opioid treatment plans.
Other initiatives include things like driving information-pushed analysis into several sclerosis, developing AI-driven techniques to help those on very low incomes with managing their funds, assisting the UN in driving its sustainable improvement aims and predict outbreaks of Zika virus.
As properly as being aware of that they had been supporting to fix some of the most tough scientific challenges struggling with our species and earth, researchers were spurred on by the fact that their get the job done also has value for IBM and their shoppers.
Mojsilovic tells me, “For example … the opioid job entails causal modeling – a actually warm topic suitable now in machine learning.
“So when we began searching at troubles exactly where causal modeling could enable, a lot of of them are in this room of social intervention, coverage development, healthcare intervention, genomics – so now you get phenomenal material to attempt out your tactics, and the massive troubles suggestions to tell you … you create a library of reusable property, which you can implement to so many issues.”
Performing on environment-scale social difficulties also aids IBM and other tech businesses to look into techniques of scaling their answers to healthy entire world-scale small business issues.
A person illustration of how this is by now getting used to assistance IBM clientele is the…