Global Artificial Intelligence Executive and Entrepreneur with an AI Phd and Strong Science and Engineering Experience
Here is short article that lays out my prediction on four areas of AI that will create waves of innovation in the coming 2-10 years, just as predictive AI and generative AI has been doing so far.
As we all know, predictive and generative AI have been at the forefront of innovation, but there are 4 emerging areas that are set to make an even bigger impact on society and industry.
The first area is Causal AI, which is being led by experts such as Judea Pearl. AI is currently not very good at understanding cause and effect relationships, but Causal AI aims to change that by focusing on the development of algorithms that can comprehend causal relationships.
The second area is Distributed AI, which is focused on building AI systems with agency and the ability to collaborate and compete with other AI systems. More specifically, an area within DAI is actually referred to as Autonomous Agents and Multi-Agent Systems (AAMAS) which has been spearheaded by experts such as Victor Lesser and Michael Georgeff to tackle this issue.
En vecka efter vårt seminarium med Amsterdam Data Collective är det dags att sammanfatta den klokskap och intryck som förmedlades
Först ett stort tack till Casper Rutjes som kom till oss och Stockholms Stadshus enbart för att hålla i presentation och dialog. Ett tack till Mårten Lindskog, AI- samordnare i Stockholms Stad som höll med fantastisk historisk lokal.
Vi låter tre röster ge uttryck för dialogen och presentationen:
”Det är spännande att få in perspektiv och erfarenheter från andra Europeiska städer i tankesmedjan. Min bild är att Amsterdam ligger i framkant i arbetet med etablering av AI som är följsam till de regleringar som väntas. Amsterdam Data Collective satte in etikarbetet i ett större sammanhang och kopplade det direkt till datakvalitet, skevheter och integritetsfrågor på ett sätt jag inte sett tidigare. Ansvarsfull AI blir då inte en administrativ kostnad utan en väg till bättre datakvalitet.”
Mårten Lindskog, AI-samordnare i Stockholms stad
“Vi behöver prata om AI ur ett flera perspektiv och ett är etik. Casper Rutjes CTO Amsterdam Data Collective, visade på många intressanta exempel och lyfte flera tankeväckande utmaningar, samt visade hur man arbetar med etisk AI I Nederländerna. Det jag tar med mig från seminariet är bland annat vikten av att arbeta i multidiciplinära team och att lyfta in flera olika perspektiv tidigt i processen för att skapa tjänster/produkter vi känner oss trygga med.”
Mandi Hallstensson, Verksamhetsutvecklare AI
“AI makes decisions based on historical data – and human history is full of injustices, biases and lessons to be learned. As we work toward a future driven by intelligent automation, we have to design ways to unlearn those injustices, correct those biases and leverage those lessons, to make sure this future is available to everyone. Today’s meeting laid a great foundation for this discussion going forward.”
Andi Kravljaca, Future Strategist, municipality of Huddinge
En robust statlig e-legitimation för att råda bot på det digitala utanförskap som i dag är ett faktum för olika grupper i samhället. Det föreslår Digg i rapporten om en säker och tillgänglig statlig e-legitimation som i dag överlämnas till regeringen. E-legitimationen som föreslås placerar Sverige i nivå med övriga Europa när det gäller att erbjuda en e-legitimation på högsta tillitsnivån.
From solving maths and science problems to translating with astonishing accuracy between hundreds of languages – not to mention generating images and videos based on a natural language prompt – AI is making strides pretty much across the board.
In this article, I’ll briefly discuss some of the most recent (and the most exciting!) developments that you should know about, but perhaps don’t already.
The paper’s main contributions are twofold: to demonstrate how to apply the general European Union’s High-Level Expert Group’s (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare; and to investigate the research question of what does “trustworthy AI” mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient’s lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia (Italy) since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection, uses socio-technical scenarios to identify ethical, technical and domain-specific issues in the use of the AI system in the context of the pandemic.
This handbook is published in the context of AI Watch, the European Commission’s knowledge service to monitor the development, uptake and impact of AI for Europe, which was launched in December 2018 as part of the Coordinated Plan on the Development and Use of Artificial Intelligence Made in Europe.
Since 2014, the European Commission has been ranking the level of digitalization in the member states. Since the start, Sweden has been in second or third place in the Union, but last year and this year, the position has been lost in favor of the Netherlands taking the bronze place. Finland tops this year’s ranking closely followed by Denmark.
