Issue #[[item.issue__number]] published [[timeFormat(item.date)]]

106 items in AI

Cool to hear a couple of well seasoned industry pro’s speak about artificial intelligence in HR Tech. Brainfooder Peter Gold in the house, taking the skeptics view. Worthy compliment to the New York City post earlier in this newsletter. It’s Chad and Cheese so of course it is unfiltered but always great
Issue #267 published 21 Nov 2021
If signed into law, it will require providers of automated employment decision tools to have those systems evaluated each year by an audit service and provide the results to companies using those systems.
Remember when every HR tech vendor put ‘AI’ into their marketing lit? Pretty much every vendor will be doing the opposite now, as the legislative environment pivots on the axis of bias reduction rather than recruiting efficiency. PS: if you want to talk about this some more, join the conversation in the fb group.
Issue #267 published 21 Nov 2021
Accessible white paper on the impact of AI on the future of work. Strikes a necessary professional balance between the utopic / dystopic appraisals of artificial intelligence and instead explains - in plain language - where we are, where we might want to go and how to get there. Download it.
Issue #266 published 14 Nov 2021
Now on its 9th anniversary, the State of AI Report by Nathan Benaich and Ian Hogarth is one of the few annuals that everyone has got to read. Talent parts are on page 75-92 if you want to skip. Read it online here, download the pdf here
Issue #262 published 17 Oct 2021
AI influencers and virtual human models are not only becoming a new trend, but their always available, scandal free immutability means that they are superior brand assets in which to invest time and resources. ‘Rozy’ isn’t going to need to take a break, send a bad tweet or - perhaps most significantly - ever age. Brainfood for sure.
Issue #259 published 26 Sep 2021
Thought provoking essay on why the implementation of AI into HR is not straightforward - human behaviour is deeply embedded in context, and not easy to abstract into algorithms. There is a way out though, and a pretty cool framework on how to get there. Essential read
Issue #256 published 5 Sep 2021
Most Indo-European languages - apart from English - are gender inflected, meaning that there are masculine and feminine (and for our German friends, also neuter!) forms of noun words, such as job titles. What impact does this have allocating recommendations based on searching on those terms? Fascinating research from the Netherlands - read the (English language) report here.
Issue #255 published 29 Aug 2021
Github Copilot might be the biggest news in software engineering this year - essentially an intelligent typo correcting, code predicting AI, powered by the work of the millions of human programmers who have solved similar problems. Some think it is the end of the programmer; almost all think that it will drive the evolution of programming. So this is a fun exercise - can it actually get a job on its own?
Issue #254 published 22 Aug 2021
CogX is the premier community for all things AI and a great deal of their talks are available on Youtube. This one, on the challenges of crafting policy for ethical AI, is excellent. Have a watch / listen
Issue #253 published 16 Aug 2021
Outstanding essay, with a shift of perspective, offering a way out of the conundrum of AI not performing the way we think it should. Main point is how humans actually make decisions is not based on more data but on less energy expenditure. Interesting reset of the argument. Have a read.
Issue #252 published 8 Aug 2021
Fascinating report on the prevalence of facial recognition technology in the United States. We have seen this technology pretty much roundly lambasted in its application in recruiting over concerns of bias and inaccuracy, so its adoption in other domains is interesting - do the same concerns apply?
Issue #251 published 1 Aug 2021
Staying with coding, the conversation in the tech world is about the future of programming itself, given the rise of AI code generators like GitHub Copilot. Vlad Iliescu, Head of AI at Strongbytes, gives first impressions….and it broadly positive. Significant ramifications for the nature of programming - and, the type of skills a programmer is going to need - in the near future.
Issue #251 published 1 Aug 2021
There’s a time and place to be “data-driven,” “data-informed,” and “data-inspired.” Shayna Stewart shares her expertise on when to leverage each mindset to help you get the most out of your data. H/T Bas van de Haterd for the share.
Issue #249 published 18 Jul 2021
It’s impossible to avoid AI in recruiting; hence important to collate as much information to support decision making on when and how to use and for what purpose. A twitter thread from a Brainfood Live on the same topic
Issue #248 published 11 Jul 2021
The innocuous sounding launch of GitHub Copilot belies its enormous potential. Here’s how it works: based on what you type, Copilot will predict what you are trying to do and automatically recommend code based on the aggregate of code other developers have used to solved similar problems.It will massively speed up software development, standardise a great deal of solution engineering, drastically reduce input errors - and very likely - change the nature of software engineering. Relevant to all of us here, especially advocates of ‘teaching kids to code’
HN thread here, whilst other developers have been more slightly more emphatic with the implications.
Issue #247 published 4 Jul 2021
4th edition of the annual Artificial Intelligence Index Report is out. High level, global view of the ‘state of AI’ from application, ethics, R&D, skills distribution and more. Massive 222 pages, so one to download (do it here) and review at leisure. One page summary on page 7 is also a decent shortcut.
Issue #244 published 13 Jun 2021
This is really a book (254 pages!) which someone needs to convert into an interactive website but I include it here because introduces some important concepts: where AI ‘sits’ in business, specifically where it should sit - at the interaction of individuals and the network. Dip and dive into this, so don’t let the length put you off. It ultimately is about the future design of organisations. Download it here
Issue #240 published 16 May 2021
There isn’t a better summariser of the complexity in HR tech and AI than brainfooder John Sumser. Here he makes the implications of EU draft legislation understandable for us . Must read, for all of us really. Leaked EU draft here if you are so inclined to read the original source material
Issue #239 published 9 May 2021
Contains apps titled ‘AI Sales Email Assistant’, ‘Copywriting Conversion’ and ‘Content Generation Engine’. If you do a lot of writing in your job, you may like (or not, actually) to check out this source site for GPT-3 apps.
Issue #238 published 2 May 2021
And speaking about data, we have got some work to do to better understand what we mean by the terms, especially when they are referring to artificial intelligence. Well organised and accessible post on a particular form of bias in AI, ‘dataset bias’. Must read folks
Issue #236 published 18 Apr 2021
Fun tool which is trying to educate, collate and yet also manipulate at the same time, unironically becoming an example of what it criticises. It’s about emotional recognition technology folks and why its bad - your results and your feedback will not doubt go into a report which will confirm the case. Bad faith stuff - but like I said, - a fun tool and not without merit. Have a play here, but keep in mind the user journey that has been mapped out for you.
Issue #235 published 11 Apr 2021
Compliance drives job creation. This is true whether you need to stay on the right side of the law, or the right side of emerging social values. Twitter have an employee (s) whose job is essentially ‘due diligence on the AI’ - contextualising the algorithmic outputs and presumably to stage judgement call interventions. A watcher / interpreter of the algorithm? Potential new career path here folks.
Issue #233 published 28 Mar 2021
Neither machines nor humans are great at knowing what they don’t know. Humans are much better at understanding and accounting for it. They work to uncover their biases. The process of disrupting technology and commerce is rooted in discovering the assumptions that limit growth and innovation. Machines, on the other hand, are best at solidifying processes and procedures
Just one amongst a number quotable lines in this outstanding essay on the problem of bias in AI. It’s brainfooder John Sumser, operating at peak. Must read
Issue #231 published 15 Mar 2021
Huge report on the ‘state of AI’, this is one to download and save for reading / referencing later. The summary on the homepage is decent for those who want to skim. Main takeaways for me are: generative applications of AI cutting deeply into ‘content’ production (any of us doing anything here?) work, continuing diversity challenge in AI and the competition for immigrant labour which maybe the determining factor for ‘winning’ the AI race
Issue #230 published 7 Mar 2021
Criticism that GPT-3 is not truly intelligent might be true but also irrelevant, as we see increasingly sophisticated implementations of the OpenAI’s protocol. This user is using GPT-3 to generate SQL queries which then produce answers to questions asked by humans. The future is in plain view.
Issue #229 published 28 Feb 2021
Fascinating experiment by journalists from Bavarian Broadcasting, who tested a video candidate assessment tool using paid actors, varying their appearance, lighting and backgrounds. No surprise that the AI was swayed by seemingly cosmetic differences. A well told story in an accessible interactive website. H/T to brainfooder Pedro Barahana in the fb group.
Issue #228 published 21 Feb 2021
No other post on AI better combined comprehensiveness to the discipline, with relevancy to our field, than this one from hubert.ai. It’s a thrilling journey on what AI is, where it started to have impact in recruiting and where it can be found now. Great read, for beginner and expert alike.
Issue #220 published 27 Dec 2020
Another week, another cool index, this time a country by country comparison on AI power. The only handicap is significant - data sources are overwhelming US centric platforms , therefore data is accordingly US centric. How many Russian data scientists on LinkedIn for example? Probably not near all of them. Fascinating to see which countries lay where though, and useful enough for those who want to identify best countries from which to source AI talent. Have a read and a bookmark, with the usual caveats 👆
Issue #218 published 13 Dec 2020
So the final post this week is relevant in context with the gendering of robots. In 60 seconds this video manages to amaze and creep out at the same time. Embodied AI is happening and perhaps there is another, more important question to be asked - do we even want embodied AI to be human-like at all? H/T brainfooder Colin McNicol for the share in the fb group
Issue #217 published 6 Dec 2020
Wonder how of this AI ‘adoption’ rate from McKinsey is just vendors upgrading software and rolling it out to existing customers. Probably most of it, but maybe I’m a cynic and should be more generous in reviewing info like this. Still, including it as there is a decent table at the end which provides something 5 point plan to increase of the to increase the efficacy of AI adoption in your business.
Issue #217 published 6 Dec 2020
We all need to read this post. It’s not specifically about recruiting but the technologies, techniques and paradigms discussed here are already having impact in the work we do. We need to be driving this car; otherwise we’re going to be ran over by it. Accessible and comprehensive - read!
Issue #216 published 29 Nov 2020
South Korean cable channel MBN has virtually replicated one of their news anchors, who then has to introduce her potential replacement. Fascinating conjecture as to who owns the replica - perhaps something we would embrace if ownership to the individual being replicated. Like we’ve said before in this newsletter, the future isn’t going to wait for us to get comfortable with it. Have a read (and watch - video embedded)
Issue #215 published 23 Nov 2020
This is an interesting experiment - a roll on / roll off ‘bot battle’ of conversational AI who compete rap battle style. It’s fascinating to observe how automated agents talk to, and learn from, each other when they do it. Future is being made and like I have said before - it isn’t waiting around for us to get comfortable with it. H/T to brainfooder Martyn Redstone for the share in the fb group
Issue #214 published 16 Nov 2020
Experience the world of face detection algorithms in this freaky test.
👆 OK, I thought and clicked on through.
Turns out to be a fascinating exercise, illustrating some of the core concepts on how facial recognition works. Also note the psychological manipulation (a.k.a marketing) techniques used throughout to get you to do it. Fun, creepy, educational,maybe risky …..so check it out. H/T to brainfooder Bas van de Haterd for the share in the fb group
Issue #210 published 18 Oct 2020
There’s not many people in our business smarter than brainfooder John Sumser. A great writer - capable of find new and important angles to describe problems which might otherwise seem intractable, yet through his exposition, offers a way out. Read this, on bias and AI….see what I mean?
Issue #209 published 11 Oct 2020
Comprehensive, accessible, essential - the State of AI report by Nathan Benaich gives amateur and expert alike a superb snapshot on where we are at on the Artificial Intelligence. You’re going to need to download it even if you don’t read it all straight away. Will be on the Brainfood Larder though, so safe to retrieve from there.
Issue #208 published 4 Oct 2020
Didn’t take long for the applications of GPT-3 to productise. Have a watch of the video on the Magic Email landing page - great demonstration of how this protocol can provide immediate value - summarising long emails in one click. Not sure what it might do to brainfood, but you might as well get on the waitlist and find out.
Issue #205 published 13 Sep 2020
Three themes emerge from this Oxford University report for failing AI implementations…1) poor integration with existing workers & working procedures, 2) overly simplistic AI i.e. binary decision tree and 3) a lack of management transparency leading to employee lack of trust. Based on newspaper reports though….is that data ok? Download and read here
Issue #204 published 6 Sep 2020
The UK’s recent GCSE and A-Level grade prediction fiasco provides a fascinating opportunity to see how prediction algorithms really work. This superb analysis is technical but accessibly written and an excellent lesson on the importance of second order thinking. Read this, if you wanted to know what an algorithm is, how it works and why it might not ‘work’ even if it does actually work.
Issue #203 published 30 Aug 2020
The optimists view of AI is that it will free human workers from the mundane so that we cam focus on the work software cannot do - work with other humans. Decent list of the skills we’re going to need to develop for this version of the future - check it out here. H/T brainfood Selma Mohr for the share in the fb group.
Issue #202 published 23 Aug 2020
Fascinating insider view from model Sinead Bovell on the rise of CGI competitors in the fashion industry - cheaper, always on-demand, always less demanding (remember Linda Evangelista’s famous quote from the noughties of ‘not getting out of bed for less than$10,000 a day’?’) and quite simply are much more efficient in putting on different outfits and making different poses. The era of the 'supermodel’ is already long gone; the era of any human model might also soon be coming to an end.
Issue #200 published 9 Aug 2020
More on OpenAI’s GPT-3. The lesson here is that AI doesn’t have to be all that smart for it to be practically useful - it just has to have a massive dataset (like, for instance, the Internet). 3 minute video on how simple commands can compile into complicated code, and run. Basically ….means the end of reinventing the wheel?
Issue #199 published 2 Aug 2020
Know his name, because ‘he’ doesn’t actually exist. Fascinating story / PR stunt by a Russian design studio who passed off the bot 'Nikolay Ironov’ as a human designer - and won awards for the work. Overlay this story of human like AI performance on top of the phase shift to remote only….and the inevitable future moves into focus.
Issue #199 published 2 Aug 2020
The engineering blog on LinkedIn contains fascinating posts on the mechanics of the platform; if you want to know how big blue works, you really have to be on it with this blog series. This post provides a detail on how the job matching algorithm works - a fascinating breakdown of the relevancy challenge. H/T to brainfooder Colin McNicol for the share in the fb group.
Issue #199 published 2 Aug 2020
Expect to hear a lot more about OpenAI’s new language model, GPT-3. Released to private beta (apply here), its a language model which can write headlines, viral tweets, poems, whole stories and even code. Might just change everything we currently do with a keyboard. Which, for us recruiters, is more or less everything. Read here, join the conversation here, and see this example of a GPT-3 generated cover letter - H/T brainfooder Christine Ng for that share. This is probably a big deal.
Issue #198 published 26 Jul 2020
That cultures change is an important idea we struggle to embed in our discourse on organisational culture. How do we reduce the distance between what we think is there, and what really is there now? The challenges for AI are also the challenge of HI - human intelligence. Great brainfood from John Sumser- have a read here
Issue #194 published 28 Jun 2020
Fascinating research tracking the career paths of AI scientists and researchers, with a particular emphasis on immigration flow; which countries produce and ‘consume’ the most AI talent? It’s another story on China and the USA. H/T to brainfooder Petar Vujosevic for the share.
Issue #193 published 21 Jun 2020
A lot has been written about AI in Recruiting, so rather handy to have most of it aggregated into a single resource. This guide is a perfect combination of comprehensive + accessible, being lengthly yet chunkable. Everyone needs to read this - do it here. H/T brainfooder Denys Dinkevych
Issue #192 published 14 Jun 2020
Outstanding write up of the Economics of Artificial Intelligence Conference 2019 from our buddies at Nesta. How will AI impact jobs, workplaces and innovation? Explore the investigation and discussion in this well linked review post.
Issue #158 published 23 Apr 2020
Fascinating experiment on the how humans interact with robots that are made in a country different from our own. Do national stereotypes project onto anthropomorphised and embodied AI? Perhaps related to the Tengai conversations we’ve been having lately in the fb group.
Issue #138 published 23 Apr 2020
Last week, Amazon quietly unveiled what could turn into a fundamentally different way to build software. Think machine learning tools ‘baked in’ to your software development. Expect massive adoption from the tech community. For the luddites, this is a further step towards to de-skilling of software engineering. It’s thought provoking stuff. Thanks to brainfooder Randy Bailey from Walmart for the share
Issue #61 published 23 Apr 2020
So Amazon created a sexist recruitment machine. Accidentally, it must be said. Excellent case study in the limitations of using historical data to produce different outcomes - it’s just going to (more efficiently) deliver the same results you had before.
Issue #105 published 23 Apr 2020
Important questions raised by Roya Pakzad in this comprehensive yet accessible breakdown of IBM’s Personality Insights tool. Problems when it work, problems when it doesn’t maybe the intractable challenge of AI. This post is of interest to anyone in sourcing, assessment, AI and ethics. That really should be all of us here really. Have a read
Issue #151 published 23 Apr 2020
Humans are never going to beat AI for accuracy and efficiency in measuring the impact of work. So we need to migrate to the work that cannot be easily recorded in a spreadsheet.
Issue #24 published 23 Apr 2020
The answer, is ‘reinforcement learning’, following on the pivotal moment in 2015 when AlphaGo, a reinforcement learning trained AI, beat Lee Sedol on Go. Excellent and accessible snapshot of the 'state of AI’ by MIT
Issue #121 published 23 Apr 2020
The hate for open plan offices has hit apogee of late, so maybe it’s time to give up on trying to design how we use space in work. How about we leave it to algorithms? Genetic algorithms to be precise, using darwinian evolution to evolve a floor plan. Someone should really give this a try.
Issue #96 published 23 Apr 2020
Humans-assisting-machines and Machines-assisting-humans, this is an optimists take on the rise of AI and RPA in the world of work. Whatever your angle, the main point is this: to optimise your value from AI, you need to redesign your operations around the reality of human-AI interaction. Read the summary here
Issue #100 published 23 Apr 2020
25,000 worldwide - that’s the number of AI folks there are on planet earth. It’s a massive shortage and AI will almost certainly be the most in-demand skillset for the next several years. H/T brainfooders Azeem Azhar and John Sumser who each independently brought this excellent interactive report into my view. Click on it, have a play. 
Issue #73 published 23 Apr 2020
Swiftian satire from Jason Collins on this essay on the double standard applied against artificial intelligence. Written for fun, but poses an important question: why do we demand from AI decision making, that which we routinely tolerate from human decision making? Have a laugh and a ponder on this delightfully wicked piece of brainfood
Issue #166 published 23 Apr 2020
Elegant website which compares the development of AI in countries across the indices of infrastructure, investment and innovation. Make no mistake - this a race - in the end, maybe the only one that is going to matter. This tool gives a guide on where we are.
Issue #166 published 23 Apr 2020
Founder effect in full display here with artificial intelligence is booming in Europe, China, and the US, but dominated by men in every location. What impact this will have? We don’t know for certain, but we can perhaps guess
Issue #114 published 23 Apr 2020
The value of past experience as a predictor of future performance still rated highly, especially by those who have that experience. And ‘bias’ seems to becoming a catch-all explainer for outcomes we don’t like. Interesting post - one that I don’t agree with - but included here because it’s definitely food for the recruiting brain. Brainfooder David D'Souza makes a good counter point, so read that also as a companion piece.
Issue #177 published 23 Apr 2020
Selection algorithms everywhere are exhibiting traits that appear to be racist, sexist, and otherwise discriminatory. Have neural networks already developed their own neuropathy? Or are people somehow the problem?
Outstanding post from ZDNET on the challenge presented by bias in AI, and ‘why AI can’t just fix it’. Lots of concepts here that we in the recruitment biz need to learn, so this one to take your time over. Fascinating, accessible and necessary read
Issue #145 published 23 Apr 2020
Supporting evidence for the idea that autonomous decision making is not only superior to human judgement, but also preferred by humans subjected to it. We might fear the robots, but we also think they are more likely to be fair. Also read the Amazon story in Issue 133
Issue #137 published 23 Apr 2020
Outstanding deck from our buddies at Allegis Global Solutions, HiringSolved and SmashFly. Clear outline of where we are and how we might apply Artificial Intelligence to augment and replace recruiters - this is a great compliment to the previous two posts on this topic. 
Issue #63 published 23 Apr 2020
Superbly informative article on AI - it’s a well categorised, deep dive yet an accessible transcription of interviews with the great and the good of the industry. The ‘Seven Themes’ is a great way to to get a helicopter view of this critically important development in society. 
Issue #63 published 23 Apr 2020
Andreesen Horowitz produced a massive interactive guidebook on AI. It was not without controversy - it was perhaps a little to ambitious in it’s attempt to be the definitive resource on the topic - but this interactive book nevertheless represents a tremendous collection of thinking on the AI landscape. 
Issue #63 published 23 Apr 2020
In a week when IBM CEO Ginni Rometty predicted a 100% AI impact to human work, its timely that element.ai published their 2019 report on on the state of AI talent across the globe. Things we know: not enough AI professionals, not enough women AI professionals (18%), small number of countries dominant and AI talent is mobile. Also complete with a handy list of ML conferences to plug into a boolean search. Take a read.
Issue #131 published 23 Apr 2020
Anatomy of an AI System - The Amazon Echo as an anatomical map of human labor, data and planetary resources.
Of interest to anyone who might still remember the wonder of the voice activated internet, and what our place is in it, as simultaneously user / consumer / producer and product in the complicated supply chain that is today’s AI. A long, challenging, wonderful read
Issue #153 published 23 Apr 2020
Five AI priorities for 2020: bringing efficiency to problem solving, upskilling, improved risk management, integrating AI into business processes, and shaping new business models. Nice interactive website from PwC, with scenarios to think about for 2020.
Issue #165 published 23 Apr 2020
What’s the real value of AI for your business? PwC put together an accessible report which combines education on the topic along with welcome opportunity sizing. It’s only a 22 pager and easily snackable. 

Issue #75 published 23 Apr 2020
A great deal of the arguments about AI in recruitment stems from semantic disagreements on terminology, effectively tarpitting any debate and rendering them valueless. This landscape / taxonomy post by Francesco Corea is one of the best I’ve read, which succinctly outlines the classifications into a super readable, super valuable post. H/T brainfooder Randy Bailey for the share in the fb group.
Issue #150 published 23 Apr 2020
So file this one under ‘stuff we know already’ but always good to get research which confirms the assumption; Data Science skills are hot, and only getting hotter, as companies and countries race to acquire the skills to power the next economic revolution.
Issue #143 published 23 Apr 2020
Pretty much the Mary Meeker for AI. Messers Nathan Benaich and Ian Hogarth published their annual report on Artificial Intelligence last week. It’s a monster 136 pager but accessible enough and required reading for anyone who cares about AI. Download it here
Issue #143 published 23 Apr 2020
You might have guessed by now that brainfood is all about condensing complex information into more consumable snacks. Few resources deliver to this value that this paper from İskender Dirik. If you care about AI at all, download and have a read. H/T to brainfooder Anna Ott for the share
Issue #108 published 23 Apr 2020
Computers are getting better at mimicking our language. What does this mean for use recruiters when software to write job ads is demonstrably more effective than we are? An ‘augmented future’ might have been overly optimistic as the path toward AI superiority now seems clear. Fascinating and accessible 5 minute video. H/T to brainfooder Stan Wasowicz for the share in the fb group
Issue #178 published 23 Apr 2020
Impressive collection of resources from McKinsey on the challenge artificial intelligence brings to the workplace. This is basically a risk management framework for the enterprise. The management speak is a bit annoying but its nevertheless worth a read, especially for ‘foodies working in corp / enterprise
Issue #135 published 23 Apr 2020
Massive report on the ‘state of AI’ in 2019, covering everything from number of conferences, papers, technical progress, govt investment and the rest. Be warned: it’s a monster of a report (nearly 300 pages) but you will want to download this for reference throughout 2020. 
Issue #167 published 23 Apr 2020
It’s a running joke in the DS community that ‘artificial intelligence’ is defined by what it can’t do yet. I share MIT’s more generous definition, brilliantly outlined here in a back-of -an-envelope style by Karen Hao. H/T brainfooders John Sumser and John Rose for the share.
Issue #110 published 23 Apr 2020
How do experts make the calculations on potential job losses through automation and AI? Interesting post from Quartz, breaking down the method behind 3 major reports (linked in the article) on the future of work. Great primer on how to read reports in era of hype and fake news.
Issue #68 published 23 Apr 2020
Outstandingly straightforward explainer on how bias can creep into the algorithm. There are no easy answers here, but an important read for anyone interested in at least being critically aware of the potential of bias in AI. Have a read here
Issue #122 published 23 Apr 2020
Sometimes you just need an extendible glossary of all the terms in data science and artificial intelligence you come across and find you need to google. This here is it - a fantastic, accessible yet respectful resource on a challenging topic none of us can afford to ignore. Bookmark it.
Issue #142 published 23 Apr 2020
Is the conversation about ‘what is AI’ is finally ready to move on from rhetoric to pragmatism? This post provides a good grounding on those who still want to argue the point. In any case, it isSuperb an interesting history of the opacity of the words 'artificial’ and 'intelligence’. Have a read here
Issue #130 published 23 Apr 2020
Nathan Benaich and Ian Hogarth channeling their inner Mary Meeker with this 156 page slide deck on the State of AI. It’s an outstanding achievement. Great resource for us here on brainfood - download the full deck here
Issue #91 published 23 Apr 2020
Incredible video of the human-to-AI conversation where you really cannot tell which is the robot and which is the person. It’s application to the recruitment industry is as obvious as it is portentous. For those who want more detail on Google Duplex, you can get it directly from the horses mouth.
Issue #83 published 23 Apr 2020
Hyperbole in the title but the phenomenon of the Chinese state rolling out society changing technology is hardly without precedent. Whilst we worry about Facebook and data privacy, China is charging ahead towards it’s own vision of the future.
Issue #83 published 23 Apr 2020
Behind the artificial intelligence personal assistants and concierges are actual people, reading e-mails and ordering Chipotle. Great article on how much human input is still required for basic tasks like scheduling a meeting. 
Issue #33 published 23 Apr 2020
John Sumser cuts through the noise of AI in industry with a simple taxonomy of AI tech tools - AI as Platform Service, Data Workbench, Microservice, Embedded, the AI First Suite, and Robotic Process Automation (RPA). We need more precise thinking like this - have a read
Issue #170 published 23 Apr 2020
I had the pleasure of attending CogX’s Festival of AI last week, here’s their primer report on the impact of AI specifically to HR and it’s well worth a scan. Thanks to brainfooder and People Analytics lead for CogX, Ian Bailie, for sending this through. 
Issue #88 published 23 Apr 2020
Accessible report from MMC Ventures & Barclays on the state of AI. For ‘foodies, the headline insight is the smoke and mirrors that is much of AI in HR tech. Worth a download and a read, especially if you’re shopping for tech this year and don’t want to be bedazzled by AI sales speak. 
Issue #126 published 23 Apr 2020
A look at how automation and AI will affect the economy and its people, places, and jobs over the next few decades. Bit of the strange website by Brookings, but there’s enough value in here for it to be worth persevering with. Check it out here
Issue #139 published 23 Apr 2020
The laws of supply/demand apply when you’re building deep tech. This is a great essay from NYT on what you have to do when you really need to recruit near genius to get the job done. 
Issue #57 published 23 Apr 2020
No one in the people business can afford to ignore AI, so this high level interactive guide on AI by McKinsey & Co will come in handy. Great exposition of a complex topic. Thanks to Laurent Garnier for the share.
Issue #117 published 23 Apr 2020
Machines Gone Wrong is a project designed to explore two questions: how humans treat AI and how AI treats humans. It’s a delightful work-in-progress website which makes complex AI conversations accessible to the laity. Essential reading for anyone interested in assessment and bias in AI.
Issue #148 published 23 Apr 2020
Forecast posts should be getting boring right around now, but if you spare 5 minutes for this one, you’ll be delighted. VentureBeat have gathered together some true A-Listers in AI, including the likes of Google AI’s Jeff Dean, PyTorch’s Soumith Chintala, Nvidia ML’s Anima Anandkumar, Kidd Lab’s Celeste Kidd, and IBM Research’s Dario Gil, and asked them about the near future of the discipline. Its a bit technical but recruiters / HR folks will learn a ton here - must read. H/T Kristina Shershun for the share in the fb group (you should probably join this).
Issue #169 published 23 Apr 2020
We’re going heavy with LinkedIn this week. Forget the skeptics and the AI pedants, this post from by Przemek Berendt has just the right balance of high / low level analysis on the topic of AI in recruiting. Probably the best post in this issue, and a must read folks
Issue #103 published 23 Apr 2020
Sometimes asking the right questions is the most important thing to do. Marko Balabanovic does a great job of it here, refocusing the workforce automation threat narrative to a more nuanced view of what roles AI systems will perform in organisations. Will they be managers, co-workers or just tools? Fascinating speculation
Issue #155 published 23 Apr 2020
Wide-ranging applications of data science bring utopian proposals of a world free from bias, but in reality, machine learning models reproduce the inequalities that shape the data they’re fed. Can programmers free their models from prejudice?
Essential content, superbly presented in an interactive website. We all need to look at this, because ‘ubiquitous AI’ will be a thing.
Issue #134 published 23 Apr 2020
Do you know what Bitcoin is? AI doesn’t, as demonstrated in this enthralling mashup of the biggest hype trains happening in recruiting and elsewhere. Added animation and soundtrack, it’s worth a blast folks. 
Issue #85 published 23 Apr 2020
No one doubts the transformation potential of Artificial Intelligence, so we need to be thinking about the demographics of the folks working in it. This report from AI Now gives a great outline as well as practical steps we can take to improve diversity in this critical segment of the workforce. H/T ‘foodie Torin Ellis for the share
Issue #147 published 23 Apr 2020
Machine vision tools like facial recognition are increasingly being used for law enforcement, advertising, and - inevitably - recruiting. It makes sense for us to have a better understanding as to how computers make these categorical decisions, which this interactive explainer post from Pew Research Center does superbly well. Must read
Issue #154 published 23 Apr 2020
Decent article on the direction we need to point our own careers. Andrew Ng, formerly Head of AI at Baidu, might have said it best - anything that takes less than 1 second of reasoning, will be automated. Think more, do less folks. 
Issue #46 published 23 Apr 2020
Fascinating report by Brookings Institute using ‘AI to assess the impact of AI’ - feeding AI patent filings into an ML algorithm and mapping the words onto human tasks. The bad news? It’s highly paid, white collar work which is most at risk. Download the full report here.
Issue #163 published 23 Apr 2020
Outstanding report from CB Insights on the State of AI. Especially interesting: AI penetration per industry segment and role of government in fostering national AI capacity. It’s a race folks, perhaps the most important one not to lose. Must read for everyone here
Issue #97 published 23 Apr 2020
We need to talk about ‘genetic diversity’ folks, because the era of designer human beings is upon us. Fascinating question posed to Genomic Predictions CEO Stephen Hsu who responds that cultural differences will likely result in different responses to genetic manipulation / selection of human beings. This is brainfood folks, so have read here
Issue #144 published 23 Apr 2020
We’ve heard a great deal about ‘algorithmic bias’ but it can be tough concept to fully understand. This interactive game ought to help - its a superbly executed demonstration on how bias in training data manifests in bias in algorithmic decision making. H/T John Rose for the share
Issue #144 published 23 Apr 2020