The balanced view algorithm

I recently participated in a meeting of computer scientists where the topic was “fake news”. The implicit assumption was that “we will do this tool x that will show people what is false information, and they will become informed.” However, after the meeting I realized this might not be enough, and in fact be naïve […]

The strategy algorithm

Introduction The purpose of the strategy algorithm is to present a simple, parsimonius, and proven method for successful creation of a corporate strategy. In corporations, the problems usually do not relate to lack of resources or options, but to complexity of having in fact too many choices. This can lead to illusion of superiority which […]

User feedback: A startup perspective

Introduction – the first-order problem The first-order problem for startups often is, they are not making something people want enough to pay for. As you can see from the CB Insights data, founders identify this as the most common reason for failure. Figure 1 Reasons for startups failure Notice the connection between 1 and 2: […]

Startups! Are you using a ‘mean’ or an ‘outlier’ as a reference point?

Introduction This post is about startup thinking. In my dissertation about startup dilemmas [1], I argued that startups can exhibit what I call as ‘reference point bias’. My evidence was emerging from the failure narratives of startup founders, where they reported having experienced this condition. The reference point bias is a false analogy where the […]

Miten startupit voisivat oikeasti ratkoa ongelmia? Näkymättömän alaluokan merkitys

Johdanto Luin mielenkiintoisen artikkelin: http://miter.mit.edu/the-unexotic-underclass/ Teesinä on, että startupit keskittyvät yhteiskunnan kannalta “vääriin” ongelmiin. Ne keskittyvät joko eliitin ongelmiin (korkeasti koulutetut kosmopoliitit) tai eksoottisiin kolmannen maailman ongelmiin, joihin usein luovat lumeratkaisuja kestävien ratkaisujen sijaan. Sen sijaan alemman keskiluokan ongelmat jätetään huomiotta: esim. työttömyys, uudelleenkouluttautuminen, sotaveteraanit (USA). Tätä kohderyhmää kuvataan näkymättömäksi “alaluokaksi”, koska startupeille he eivät ole […]

Experimenting with IBM Watson Personality Insights: How accurate is it?

Introduction I ran an analysis with IBM Watson Personality Insights. It retrieved my tweets and analyzed their text content to describe me as a person. Doing so is easy – try it here: https://personality-insights-livedemo.mybluemix.net/ I’ll briefly discuss the accuracy of the findings in this post. TL;DR: The accuracy of IBM Watson is a split decision […]

The black sheep problem in machine learning

Just a picture of a black sheep. Introduction. Hal Daumé III wrote an interesting blog post about language bias and the black sheep problem. In the post, he defines the problem as follows: The “black sheep problem” is that if you were to try to guess what color most sheep were by looking and language […]

How to teach machines common sense? Solutions for ambiguity problem in artificial intelligence

Introduction The ambiguity problem illustrated: User: “Siri, call me an ambulance!” Siri: “Okay, I will call you ‘an ambulance’.” You’ll never reach the hospital, and end up bleeding to death. Solutions Two potential solutions: A. machine builds general knowledge (“common sense”) B. machine identifies ambiguity & asks for clarification from humans The whole “common sense” […]