or how our digital assistant got her name:

In Norse mythology, Elli is a personification of old age who, in the Prose Edda book Gylfaginning, defeats God Thor in a wrestling match.  She is the embodiment of the crone and the wisdom and strength of the elderly.

There are a lot of strong Goddesses to be found in Norse mythology, but Elli, nicknamed ‘the Giant Crone,’ takes the cake.  She challenged the God Thor to a wrestling match — and won.  We have to be fair to Thor though, as the whole thing turned out to be a bit of a trick.  Elli, although the weakest of the giantesses of Utgardr, was actually the personification of old age.  After the giantesses told Thor about their stunt, he obviously wasn’t too happy, even though the fact that Elli only managed to get Thor down to one knee was a mark of his strength.

This serves as a valuable lesson not to underestimate old people.  We often think of the elderly as unfit, forgetful and out of touch with modern times, but they have a wealth of knowledge and can often give good advice.  They are also not necessarily as helpless as we imagine ..

Elli is not mentioned in any other extant source but the notion that not even the Gods are immune to the effects of aging is supported by the fact that they must consume the apples of Idunn on a regular basis in order to remain young.

(Nordic wiccan blogspot)

Za nas, pa za druge pedantneže, povzemam smernice etičnega AI razvoja, ki jih načrtuje EU.

The Principle of Beneficence: “Do Good”

AI systems should be designed and developed to improve individual and collective wellbeing. AI systems can do so by generating prosperity, value creation and wealth maximization and sustainability. At the sametime, beneficent AI systems can contribute to wellbeing by seeking achievement of a fair, inclusive and peaceful society, by helping to increase citizen’s mental autonomy, with equal distribution of economic, social and political opportunity. AI systems can be a force for collective good when deployed towards objectives like: the protection of democratic process and rule of law; the provision of common goods and services at low cost and high quality; data literacy and representativeness; damage mitigation and trust optimization towards users; achievement of the UN Sustainable Development Goals or sustainability understood more broadly, according to the pillars of economic development, social equity, and environmental protection10. In other words, AI can be a tool to bring more good into the world and/or to help with the world’s greatest challenges.

The Principle of Non maleficence: “Do no Harm”

AI systems should not harm human beings. By design, AI systems should protect the dignity, integrity, liberty, privacy, safety, and security of human beings in society and at work. AI systems should not threaten the democratic process, freedom of expression, freedoms of identify, or the possibility to refuse AI services. At the very least, AI systems should not be designed in a way that enhances existing harms or creates new harms for individuals. Harms can be physical, psychological, financial or social. AI specific harms may stem from the treatment of data on individuals (i.e. how it is collected, stored, used, etc.). To avoid harm, data collected and used for training of AI algorithms must be done in a way that avoids discrimination, manipulation, or negative profiling. Of equal importance, AI systems should be developed and implemented in a way that protects societies from ideological polarization and algorithmic determinism. Vulnerable demographics (e.g. children, minorities, disabled persons, elderly persons, or immigrants) should receive greater attention to the prevention of harm, given their unique status in society. Inclusion and diversity are key ingredients for the prevention of harm to ensure suitability of these systems across cultures, genders, ages, life choices, etc. Therefore not only should AI be designed with the impact on various vulnerable demographics in mind but the above mentioned demographics should have a place in the design process (rather through testing, validating, or other). Avoiding harm may also be viewed in terms of harm to the environment and animals, thus the development of environmentally friendly11 AI may be considered part of the principle of avoiding harm. The Earth’s resources can be valued in and of themselves or as a resource for humans to consume. In either case it is necessary to ensure that the research, development, and use of AI are done with an eye towards environmental awareness.12

The Principle of Autonomy: “Preserve Human Agency”

Autonomy of human beings in the context of AI development means freedom from subordination to, or coercion by, AI systems. Human beings interacting with AI systems must keep full and effective self-determination over themselves. If one is a consumer or user of an AI system this entails a right to decide to be subject to direct or indirect AI decision making, a right to knowledge of direct or indirect interaction with AI systems, a right to opt out and a right of withdrawal.13 Self-determination in many instances requires assistance from government or non-governmental organizations to ensure that individuals or minorities are afforded similar opportunities as the status quo. Furthermore, to ensure human agency, systems should be in place to ensure responsibility and accountability. It is paramount that AI does not undermine the necessity for human responsibility to ensure the protection of fundamental rights.

The Principle of Justice: “Be Fair”

For the purposes of these Guidelines, the principle of justice imparts that the development, use, and regulation of AI systems must be fair. Developers and implementers need to ensure that individuals and minority groups maintain freedom from bias, stigmatisation and discrimination. Additionally, the positives and negatives resulting from AI should be evenly distributed, avoiding to place vulnerable demographics in a position of greater vulnerability and striving for equal opportunity in terms of access to education, goods, services and technology amongst human beings, without discrimination. Justice also means that AI systems must provide users with effective redress if harm occurs, or effective remedy if data practices are no longer aligned with human beings’ individual or collective preferences. Lastly, the principle of justice also commands those developing or implementing AI to be held to high standards of accountability. Humans might benefit from procedures enabling the benchmarking of AI performance with (ethical) expectations.

The Principle of Explicability: “Operate transparently”

Transparency is key to building and maintaining citizen’s trust in the developers of AI systems and AI systems themselves. Both technological and business model transparency matter from an ethical standpoint. Technological transparency implies that AI systems be auditable,14 comprehensible and intelligible by human beings at varying levels of comprehension and expertise. Business model transparency means that human beings are knowingly informed of the intention of developers and technology implementers of AI systems. Explicability15 is a precondition for achieving informed consent from individuals interacting with AI systems and in order to ensure that the principle of explicability and non-maleficence are achieved the requirement of informed consent should be sought. Explicability also requires accountability measures be put in place. Individuals and groups may request evidence of the baseline parameters and instructions given as inputs for AI decision making (the discovery or prediction sought by an AI system or the factors involved in the discovery or prediction made) by the organisations and developers of an AI system, the technology implementers, or another party in the supply chain.

Na naslednji način so se končali trije od štirih razpisov, na katerih smo nazadnje sodelovali. Jasno, da so merila še vedno vedno ekonomsko najugodnejša ponudba. In jasno, da stroške priprave dokumentacije, ki vključuje plačljive zunanje storitve, recimo bonitetne, ki “ne obstajajo”, krijejo ponudniki sami. Jasno tudi, da pravne službe in projekte pisarne, ki razpise pripravljajo, ne pridejo na “črno listo” pripravljalcev razpisev, kot lahko nanjo pridemo ponudniki. Tolk o izboljšavah javnega naročanja .-)


(skrajšano iz odločbe)

 

ODLOČITEV O ZAVRNITVI VSEH PONUDB

  1. Zavrnejo se vse ponudbe oddane v postopku javnega naročila št. XXXX-XX/2018
  2. Naročnik bo po izteku pravnomočnosti izvedel nov postopek oddaje javnega naročila.

O b r a z l o ž i t e v :

Naročnik je pri pregledovanju in ocenjevanju ponudb ugotovil, da dokumentacija v zvezi z oddajo javnega naročila ni bila pripravljena optimalno, zaradi česar jo mora naročnik v določenih delih spremeniti. Spremembe se nanašajo predvsem na obrazec »Predračun« in na predložitev vrste dokazila za izpolnjevanje ekonomskega in finančnega položaja. Naročnik je zahteval, da morajo ponudniki vpisati cene, zaokrožene na dve decimalni mesti, pri tem pa naročnik celic ni pravilno oblikoval, da bi to ponudnikom omogočil, hkrati pa je ponudnikom prepovedal spreminjati vsebino predračuna. Naročnik je kot dokazilo za izpolnjevanje ekonomskega in finančnega položaja zahteval obrazec S.BON-2, ki pa ne obstaja. Ker gre za napako naročnika, bo naročnik po izteku pravnomočnosti izvedel nov postopek oddaje javnega naročila ter napake odpravil.

Naročnik je predmetno odločitev sprejel na podlagi petega odstavka 90. člena ZJN-3, ki mu omogoča, da po izteku roka za odpiranje ponudb zavrne vse ponudbe, ki so prispele v postopku javnega naročanja. V skladu s splošnim sprejetim stališčem takšna odločitev naročnika ni zgolj izjemna možnost, temveč ena od legitimnih možnosti zaključka postopka, ki je ostalim načinom povsem enakovredna in prirejena.

Na podlagi navedenega je tako treba zavzeti stališče, da lahko naročnik vedno prekine postopek oddaje javnega naročila in ga zaključi brez izbire najugodnejše ponudbe, celo v primeru, če je do nemožnosti izbire prišlo zaradi njegove lastne napake, pod pogojem, da je takšna odločitev sprejeta ob spoštovanju temeljnih pravil prava Evropske unije o javnem naročanju, zlasti načela enake obravnave.

S tem je naročnikova odločitev, kot je razvidno iz izreka, utemeljena.

 

Pravni pouk:

Zoper to odločitev lahko ponudnik v roku pet delovnih dni od prejema te odločitve vloži zahtevek za revizijo, .. Taksa za vložitev zahtevka za revizijo znaša 1.000,00 EUR.

And for Thanks. To Tom Robbins. The author who turns sad nights into bright ones. The author who is an endless source of inspiration. To work. To write. To live. With quotes at the end of our pages, we thank him and nod in awe, not only to him, but also to the red beet, the sock, the satyr and the badger. Well, badgers in general 🙂

Tom Robbins has been called “a vital natural resource” by The Portland Oregonian, “one of the wildest and most entertaining novelists in the world” by the Financial Times of London, and “the most dangerous writer in the world today” by Fernanda Pivano of Italy’s Corriere della Sera. A Southerner by birth, Robbins has lived in and around Seattle since 1962. (Biography by bookbrowse.com)

Je za zmerno majhen oblikovalski studio nenavadno, da je polovica zaposlenih administrativen kader? Pišejo, berejo, kopirajo, izpolnjujejo obrazce. Več razlogov je za to, eden je ta, da se občasno udeležujemo javnih razpisov.

 

Recimo zadnjič na enem zmagamo. Dobro ocenjena je bila predložena idejna zasnova, slabše cenovna ponudba, pa vseeno za las zmagamo. Drugouvrščeni ponudnik vloži zahtevo po reviziji postopka in razloži sumljivost izbora z majhnim odstopanjem v skupnem številu točk.

 

Naročnik se odzove  z utemeljitvijo, da je sestavil žirijo iz notranjih in zunanjih sodelavcev organizacije in zaprosil DOS, da imenuje strokovnega člana, imenovali so izkušenega oblikovalca in prejemnika Prešernove nagrade. Razen tega so prijave ocenjevali anomimno. Vse skupaj se mi, milo rečeno, po udeležbi na desetinah podobnih razpisov, zdi nenavadno higienično.

 

Kakorkoli, revizijska komisija se po dveh mesecih odloči, da je naročnik kršil načeli transparentnosti javnega naročanja in enakopravne obravnave ponudnikov in se razpis razveljavi. To je povezano s plačilom revizije in stroški priprave novega naročila. Verjetno tudi s tem, da mi v ponovljenem postopku ne bomo izvajalec projekta.

 

Zakaj ta odločitev? Revizijci razlagajo, da zato, ker naročnik izbora oz. podeljenih točk pri idejnih zasnovah ni dovolj dobro utemeljil. Kaj bi bila dovolj dobra utemeljitev? Tega na revizijski komisiji sicer ne vedo, kar v odločbi priznajo, vedo pa, da utemeljitev ni bila dovolj konkretizirana. Strokovna žirija, ki jo je imanoval razpisovalec, je svojo oceno utemeljila z navedbo, da zgradba in hierarhije elementov gradiva ne ustrezata sporočilu gradiva, grafična postavitev pa ni bila ustrezno organizirana. Ni pa navedla, citiram »kaj konkretno naj bi bilo neutemeljenega pri uporabi trikotnih površin in diagonal, niti ni bilo mogoče preizkusiti, zakaj naj bi bila za neustrezno označena uporaba slikovnega materiala in kakšne natanko naj bi bile pomanjkljivosti naslovnice … ».

 

Si predstavljate delo te žirije, če bi želela točkovanje utemeljiti tako, da bi se revizijski komisiji zdelo dovolj konkretizirano? Začeti bi morala … s čim? S pametnim in za ta primer relevantnim povzetkom celotne teorije predmeta grafično oblikovanje prvega letnika ALUO? Pravzaprav mi pridejo, po daljšem razmisleku, na misel morda trije strokovnjaki, ki bi bili take utemeljitve sposobni v kakem tednu, kolikor je bilo časa.

 

V glavnem. V vsej solati nepreglednih, slabo sestavljenih in slabo izvedenih javnih naročil, zakaj mi pride najprej na misel to za maketo drugega tira, kjer excel ni računal prav in so izbrali ponudnika z dvojno ceno, ne da bi to kdorkoli ugotovil … kakšno korist imamo državljani, ponudniki in naročniki od revizijske komisije, ki lastnega mnenja nima in to prizna, ni ga tudi pripravljena prepustiti stroki, ki je tokrat pravilno in izjemoma bila rekrutirana, ampak odloči po načelu najmanjšega tveganja zase: razveljaviti in ponoviti naročilo. Ni prvič. Navajam zadnji primer.

Belgijci delajo kislo pivo po sistemu, da v ohlajeno pivo padajo mikroorganizmi iz zraka, s sten, iz lesa z mušicami. To proizvajajo v istih kleteh že sto in več let, zato se je vzpostavila takšna mikroflora, ki je konstantna. Pri nas primarno fermentacijo, ki je zelo burna, najprej opravimo v posodah iz inoksa, traja pa od enega tedna do enega meseca, odvisno od tega, katere mikroorganizme dodamo. Če bi to zvarjeno pivo takoj prelili v sode, bi fermentacija vse izbruhala iz soda. Tako pa že delno fermentirano pivo natočimo v hrastove sode, v katerih se pivo začne starati in šele pri sekundarni fermentaciji, ki ji po potrebi dodajamo nove mikroorganizme, pridobivati svoj značilni kiselkasti okus. Mi pravzaprav proizvajamo kraft pivo, ki ga staramo in spreminjamo s svojimi mikrobiološkimi dodatki.

Miha Tome, Dnevnik, 10. januarja 2018

Obsedenost z zgodnjim bluesom, iskanje peščice preživelih gramofonskih plošč iz 20-ih let prejšnjega stoletja po ameriškem globokem jugu, mogočni ostanki samo formalno preminulega sužnjelastništva in duše, ki se manj resno kot danes držijo vedno istega telesa. Vrhunec poletnega branja z vprašanjem, kako Hari Kunzru v pičlih treh letih po Bogovih brez ljudi servira tako epsko delo. Z jajci.

Pa še sodobna definicija privatne lastnine, stran 40: “… I think the meaning of private property had never quite sunk in for me until then; its weight, its peculiar authority. Privacy was disconnection, the power to take a section of the world offline.

author: Hari Kunzru
title: White tears
Hamish Hamilton, Penguin books