Every person engaged with the networked world constantly creates rivers of data. We do this in ways we are aware of, and ways that we aren’t. Corporations are eager to take advantage.
Take, for instance, NumberEight, a startup, that, according to Wired, “helps apps infer user activity based on data from a smartphone’s sensors: whether they’re running or seated, near a park or museum, driving or riding a train.” New services based on such technology, “will combine what they know about a user’s activity on their own apps with information on what they’re doing physically at the time.” With this information, “instead of building a profile to target, say, women over 35, a service could target ads to ‘early risers.’”
Such ambitions are widespread. As this recent Harvard Business Review article puts it, “Most CEOs recognize that artificial intelligence has the potential to completely change how organizations work. They can envision a future in which, for example, retailers deliver individualized products before customers even request them—perhaps on the very same day those products are made.” As corporations use AI in more and more distinct domains, the article foretells, “their AI capabilities will rapidly compound, and they’ll find that the future they imagined is actually closer than it once appeared.”
Even today, let alone in such a future, technology can completely obliterate privacy. Coming up with laws and policies to stop it from doing so is a vital task for governments.As the Biden administration and Congress contemplate federal privacy legislation they must not succumb to a common fallacy. Laws guarding the privacy of people’s data are not only about protecting individuals. They are also about protecting our rights as members of groups—as part of society as a whole.
The harm to any one individual in a group that results from a violation of privacy rights might be relatively small or hard to pin down, but the harm to the group as a whole can be profound. Say Amazon uses its data on consumer behavior to figure out which products are worth copying and then undercuts the manufacturers of products it sells, like shoes or camera bags. Though the immediate harm is to the shoemaker or the camera-bag maker, the longer-term—and ultimately more lasting—harm is to consumers, who are robbed over the long run of the choices that come from transacting in a truly open and equitable marketplace. And whereas the shoemaker or camera-bag manufacturer can try to take legal action, it’s much tougher for consumers to demonstrate how Amazon’s practices harm them.
This can be a tricky concept to understand. Class action lawsuits, where many individuals join together even though each might have suffered only a small harm, are a good conceptual analogy. Big tech companies understand the commercial benefits they can derive from analyzing the data of groups while superficially protecting the data of individuals through mathematical techniques like differential privacy. But regulators continue to focus on protecting individuals or, at best, protected classes like people of particular genders, ages, ethnicities, or sexual orientations.
If an algorithm discriminates against people by sorting them into groups that do not fall into these protected classes, antidiscrimination laws don’t apply in the United States. (Profiling techniques like those Facebook uses to help machine-learning models sort users are probably illegal under European Union data protection laws, but this has not yet been litigated.) Many people will not even know that they were profiled or discriminated against, which makes it tough to bring legal action. They no longer feel the unfairness, the injustice, firsthand—and that has historically been a precondition to launching a claim.
Individuals should not have to fight for their data privacy rights and be responsible for every consequence of their digital actions. Consider an analogy: people have a right to safe drinking water, but they aren’t urged to exercise that right by checking the quality of the water with a pipette every time they have a drink at the tap. Instead, regulatory agencies act on everyone’s behalf to ensure that all our water is safe. The same must be done for digital privacy: it isn’t something the average user is, or should be expected to be, personally competent to protect.
There are two parallel approaches that should be pursued to protect the public.
One is better use of class or group actions, otherwise known as collective redress actions. Historically, these have been limited in Europe, but in November 2020 the European parliament passed a measure that requires all 27 EU member states to implement measures allowing for collective redress actions across the region. Compared with the US, the EU has stronger laws protecting consumer data and promoting competition, so class or group action lawsuits in Europe can be a powerful tool for lawyers and activists to force big tech companies to change their behavior even in cases where the per-person damages would be very low.
Class action lawsuits have most often been used in the US to seek financial damages, but they can also be used to force changes in policy and practice. They can work hand in hand with campaigns to change public opinion, especially in consumer cases (for example, by forcing Big Tobacco to admit to the link between smoking and cancer, or by paving the way for car seatbelt laws). They are powerful tools when there are thousands, if not millions, of similar individual harms, which add up to help prove causation. Part of the problem is getting the right information to sue in the first place. Government efforts, like a lawsuit brought against Facebook in December by the Federal Trade Commission (FTC) and a group of 46 states, are crucial. As the tech journalist Gilad Edelman puts it, “According to the lawsuits, the erosion of user privacy over time is a form of consumer harm—a social network that protects user data less is an inferior product—that tips Facebook from a mere monopoly to an illegal one.” In the US, as the New York Times recently reported, private lawsuits, including class actions, often “lean on evidence unearthed by the government investigations.” In the EU, however, it’s the other way around: private lawsuits can open up the possibility of regulatory action, which is constrained by the gap between EU-wide laws and national regulators.
Which brings us to the second approach: a little-known 2016 French law called the Digital Republic Bill. The Digital Republic Bill is one of the few modern laws focused on automated decision making. The law currently applies only to administrative decisions taken by public-sector algorithmic systems. But it provides a sketch for what future laws could look like. It says that the source code behind such systems must be made available to the public. Anyone can request that code.
Importantly, the law enables advocacy organizations to request information on the functioning of an algorithm and the source code behind it even if they don’t represent a specific individual or claimant who is allegedly harmed. The need to find a “perfect plaintiff” who can prove harm in order to file a suit makes it very difficult to tackle the systemic issues that cause collective data harms. Laure Lucchesi, the director of Etalab, a French government office in charge of overseeing the bill, says that the law’s focus on algorithmic accountability was ahead of its time. Other laws, like the European General Data Protection Regulation (GDPR), focus too heavily on individual consent and privacy. But both the data and the algorithms need to be regulated.
The need to find a “perfect plaintiff” who can prove harm in order to file a suit makes it very difficult to tackle the systemic issues that cause collective data harms.
Apple promises in one advertisement: “Right now, there is more private information on your phone than in your home. Your locations, your messages, your heart rate after a run. These are private things. And they should belong to you.” Apple is reinforcing this individualist’s fallacy: by failing to mention that your phone stores more than just your personal data, the company obfuscates the fact that the really valuable data comes from your interactions with your service providers and others. The notion that your phone is the digital equivalent of your filing cabinet is a convenient illusion. Companies actually care little about your personal data; that is why they can pretend to lock it in a box. The value lies in the inferences drawn from your interactions, which are also stored on your phone—but that data does not belong to you.
Google’s acquisition of Fitbit is another example. Google promises “not to use Fitbit data for advertising,” but the lucrative predictions Google needs aren’t dependent on individual data. As a group of European economists argued in a recent paper put out by the Centre for Economic Policy Research, a think tank in London, “it is enough for Google to correlate aggregate health outcomes with non-health outcomes for even a subset of Fitbit users that did not opt out from some use of using their data, to then predict health outcomes (and thus ad targeting possibilities) for all non-Fitbit users (billions of them).” The Google-Fitbit deal is essentially a group data deal. It positions Google in a key market for heath data while enabling it to triangulate different data sets and make money from the inferences used by health and insurance markets.
What policymakers must do
Draft bills have sought to fill this gap in the United States. In 2019 Senators Cory Booker and Ron Wyden introduced an Algorithmic Accountability Act, which subsequently stalled in Congress. The act would have required firms to undertake algorithmic impact assessments in certain situations to check for bias or discrimination. But in the US this crucial issue is more likely to be taken up first in laws applying to specific sectors such as health care, where the danger of algorithmic bias has been magnified by the pandemic’s disparate impacts on US population groups.
In late January, the Public Health Emergency Privacy Act was reintroduced to the Senate and House of Representatives by Senators Mark Warner and Richard Blumenthal. This act would ensure that data collected for public health purposes is not used for any other purpose. It would prohibit the use of health data for discriminatory, unrelated, or intrusive purposes, including commercial advertising, e-commerce, or efforts to control access to employment, finance, insurance, housing, or education. This would be a great start. Going further, a law that applies to all algorithmic decision making should, inspired by the French example, focus on hard accountability, strong regulatory oversight of data-driven decision making, and the ability to audit and inspect algorithmic decisions and their impact on society.
Three elements are needed to ensure hard accountability: (1) clear transparency about where and when automated decisions take place and how they affect people and groups, (2) the public’s right to offer meaningful input and call on those in authority to justify their decisions, and (3) the ability to enforce sanctions. Crucially, policymakers will need to decide, as has been recently suggested in the EU, what constitutes a “high risk” algorithm that should meet a higher standard of scrutiny.
The focus should be on public scrutiny of automated decision making and the types of transparency that lead to accountability. This includes revealing the existence of algorithms, their purpose, and the training data behind them, as well as their impacts—whether they have led to disparate outcomes, and on which groups if so.
The public has a fundamental right to call on those in power to justify their decisions. This “right to demand answers” should not be limited to consultative participation, where people are asked for their input and officials move on. It should include empowered participation, where public input is mandated prior to the rollout of high-risks algorithms in both the public and private sectors.
Finally, the power to sanction is key for these reforms to succeed and for accountability to be achieved. It should be mandatory to establish auditing requirements for data targeting, verification, and curation, to equip auditors with this baseline knowledge, and to empower oversight bodies to enforce sanctions, not only to remedy harm after the fact but to prevent it.
The issue of collective data-driven harms affects everyone. A Public Health Emergency Privacy Act is a first step. Congress should then use the lessons from implementing that act to develop laws that focus specifically on collective data rights. Only through such action can the US avoid situations where inferences drawn from the data companies collect haunt people’s ability to access housing, jobs, credit, and other opportunities for years to come.
Improved husbandry of marine invertebrates using an innovative filtration technology – part two: results with two 12 cubic meter DyMiCo systems
As the marine ecosystems of our planet slowly dwindle, the demand for marine life from the aquarium industry puts evermore pressure on wild populations. With climate change wreaking havoc on coral reefs, and ocean acidification looming on the horizon, the importance of sustainable aquaculture is increasing rapidly. Fortunately, there are growing efforts to culture a myriad of marine and freshwater species. Some species, however, are lagging behind despite high demand from the aquarium industry. As detailed in part one, so-called filter and suspension feeding organisms that rely heavily on live plankton do not fare well in closed systems. These include many species of sponges, corals and echinoderms, which are interesting candidates for sustainable aquaculture. Filtration systems that are designed to maintain plankton populations and high water quality simultaneously may be an important step to increase the number of species that can be aquacultured.
In part one I introduced DyMiCo (Dynamic Mineral Control) as an alternative to systems using foam fractionators or common biofilters, to allow the buildup of a plankton population. Several institutions have been using DyMiCo over the last decade, including Rotterdam Zoo and Wageningen University (The Netherlands), Antwerp Zoo (Belgium), and NAUSICAA (France). The systems at these institutions have been running for up to eight years straight, with flourishing marine life. In early 2011, two DyMiCo systems were set up as part of an experimental coral nursery project in Utrecht, The Netherlands (see www.ecocoral.eu). These systems each have a volume of 12 m3 or 3,158 USG and hold many invertebrates including approximately 3,000 scleractinian corals in total. One of these systems was stocked with several invertebrates whose husbandry has proven highly difficult, in order to assess their response to DyMiCo. These included sponges (Trikentrion flabelliforme), gorgonian octocorals (e.g. Guaiagorgia sp.), hydrozoans (Distichopora spp.) and Comatulid crinoids. Below I will give an overview of the observations on both systems, in terms of water quality, plankton abundance and the welfare of the aforementioned invertebrates.
Various water parameters were measured once a week. Inorganic nutrients, i.e. ammonium, nitrate and phosphate, were measured with a spectrophotometer. ICP-AES and ICP-MS, short for inductively coupled plasma atomic emission spectroscopy/mass spectrometry, were used to determine a wide range of chemical elements in the water. Most water parameters were quite stable throughout the year. This was most likely the result of low stocking densities.
Ammonium, nitrate and phosphate were low throughout the year, even though no water changes were performed. Calcium, magnesium and alkalinity were very high due to the DyMiCo reactor, which as described in part one functions as a calcium reactor. Several trace elements (i.e. metals) were present in concentrations which exceeded those of seawater (Spotte 1992), which was likely due to the chemical composition of the artificial salt used. These included potassium, barium, cadmium, cobalt, chromium, copper, iron, lanthanum, lead, antimony and tin. Although the aquarium industry heavily promotes the dosage of various trace elements to home aquaria, it seems that without the proper analytical methods, the home aquarist may overdose a wide range of potentially toxic elements. Strontium, boron, aluminium, manganese, arsenic, lithium, molybdenum, nickel and selenium were lower in concentration when compared to seawater, and some of these elements were below the detection limit of the mass spectrometer. Despite the imbalances measured, life in the systems flourished. This may have to do with the thriving plankton population, which is known to contain high amounts of trace elements next to organic carbon, nitrogen and phosphorus, as bacteria, algae and crustaceans accumulate elements from the seawater (Martin and Knauer 1973). This may also explain the concentration decrease of certain elements. It is promising to observe that without water changes, many water parameters such as calcium, magnesium, alkalinity, nitrate and phosphate remain stable around levels considered acceptable to marine organisms.
The pH in both systems also remained fairly stable at 8.1±0.1, even though no foam fractionator or air stones were used. This was most likely the result of low stocking densities, a large water surface area and adequate surface flow, the latter two promoting gas exchange. Temperature was maintained around 26 degrees Celsius (79 degrees Fahrenheit) by heating or ventilating the room, depending on environmental conditions. Salinity was highly stable at 35 g L-1, resulting from an automated top-off system connected to a RO/DI unit.
To spur the initial buildup of a plankton population, several commercial products were dosed three times per week. Although DyMiCo produces its own plankton, which is seeded by the introduction of live rock and corals, it is important to aid the system when grazing pressure is high. In other words, as the ratio between live animals and system water is increased to an unnaturally high level, the demand for food particles invariably follows suit. Products that were used included Phyto Feast live, containing five different types of live phytoplankton, Oyster Feast, a homogenate of oyster ovarian tissue and eggs, live adult Tigriopus californicus copepods and various frozen and dried feeds (Table 1).
After several months, copepods and their nauplii swarmed throughout the system, especially at night. Small unidentified shrimps were also present. During several weeks, one system was dominated by ephyra larvae of an identified species, possibly a hydrozoan. This vibrant population of zooplankton indicated that phyto- and or bacterioplankton were available in sufficient quantities, as copepods and other crustaceans grew and reproduced.
(ml or g)
(feedings system-1 week-1)
|* feedings system-1 year-1|
|Phyto Feast Live||live||100 ml||3||Reed Mariculture, USA|
|Oyster Feast||refrigerated||100 ml||3||Reed Mariculture, USA|
|Tigriopus californicus||live||500 ml||3*||Reed Mariculture, USA|
|Rotifers||frozen||21 g||3||Ruto B.V., The Netherlands|
|Copepods||frozen||21 g||3||Ruto B.V., The Netherlands|
|Porphyra sp.||dried||1.4 g||2||Granfood B.V., The Netherlands|
High water quality and a vibrant plankton population resulted in thriving invertebrates. The species discussed below usually wither and die in the gin-clear waters of heavily filtered systems. Although these animals have only been growing in this system for a year, the results have been tantalizing.
Although different species of sponges have been growing in the system, there is one that is truly fascinating. This sponge is referred to by the scientific name Trikentrion flabelliforme, and was introduced deliberately. T. flabelliforme is a sponge that is becoming increasingly popular in the international trade. Known under the dubious trivial name Spider Sponge, this species is fascinating in the sense that it has formed a symbiosis with a hexacoral from the genus Parazoanthus (order Zoanthidea). T. flabelliforme belongs to the largest class within the phylum Porifera known as the Demospongiae, and is found in the Arafura Sea, a shallow body of water sandwiched between Australia and New Guinea. It is a typical filter feeder as it uses its choanocytes or collar cells to filter particles and dissolved substances from the seawater. Its coral symbiont is very likely Parazoanthus swiftii, as this species is the only coral known to associate with sponges from the order Poecilosclerida, to which T. flabelliforme belongs (Swain and Wulff 2007). P. swiftii is a suspension feeder as its polyps capture food particles from the water. Individual polyps are connected by common tissue known as coenenchyme or coenosarc, in the form of horizontal bridges or stolons.
The tissue of Parazoanthus is connected to the skin or pinacoderm of its host sponge, with tissue integration varying between different combinations of sponge and coral species. The physical integration between T. flabelliforme and P. swiftii seems to be superficial, in contrast to Epizoanthus spp. which may penetrate deeper into sponge tissue. The latter morphology, according to researchers, suggests a mutualistic symbiosis from which both partners benefit. The exact nature of the symbiosis between T. flabelliforme and P. swiftii is not yet clear. Parasitism seems a likely option, where the symbiotic coral benefits at the expense of its host sponge. For example, the coral may impair the sponge’s ability to pump water through its system, which is vital to sponge nutrition, waste removal and gas exchange. Commensalism is also possible, where the coral benefits while having a neutral effect on the sponge.
Although many hobbyists have tried to maintain this sponge, its survival record in closed aquarium systems has been poor. This is most likely the result of malnutrition, as this sponge and its symbiont heavily rely on food particles and dissolved organic carbon. Sponges are known to filter the smallest food particles from the water, including viruses, bacteria and phytoplankton, which are all below 10 microns (µm) in diameter. For reference: a single Artemia nauplius, which already seems small to the naked eye, measures roughly 440 µm in length. Another major part of the sponge diet is composed of dissolved organic carbon or DOC (De Goeij et al. 2009). Picoplankton (0.2-2 µm) and nanoplankton (2-20 µm) may not be available in closed systems in sufficient quantities, possibly the result of foam fractionating and overstocking of invertebrates. The coral symbiont requires zooplankton or detritus in sufficient quantities, and may feed on rotifers (e.g. Brachionus plicatilis), copepods (e.g. Tigriopus sp.), Brine shrimp (Artemia salina) and their nauplii.
T. flabelliforme has been growing in the system for a year now, and shows signs of health. Its symbiotic Parazoanthus polyps are often well expanded, especially after a batch of plankton is introduced. Although I have not been able to accurately measure growth, by e.g. determining specific growth rate, the two colonies I have observed seemed to gain volume.
Due to reorganization of the system, I have kept this sponge under several distinct microenvironments; strong (> 10 cm s-1) or weak (< 5 cm s-1) water flow rates, with moderate or low light intensity. It seems to prefer stronger water currents, although I cannot substantiate this. The presence of light, at least moderate irradiances (< 100 µm m-2 s-1), do not seem to harm the sponge or its symbiont. However, fouling organisms such as algae and cyanobacteria may take hold over the colony when it is weakened or damaged. Therefore, shading this sponge from direct light may be favorable.
Next to sponges, hydrocorals have been growing in the system over the last year. These invertebrates are not too popular in the ornamental trade, which may have to do with their difficult husbandry. Hydrocorals are not true corals, which is why they do not belong to the Anthozoa class. They are placed in a completely different class within the phylum Cnidaria, namely the Hydrozoa. There are two families within the Hydrozoa that contain coral-like species; the Milleporidae or Fire corals, and the Stylasteridae or Lace corals. Hydrocorals are often mistaken for scleractinian corals because they have a hard, calcareous skeleton, but they are only similar in appearance. Unlike scleractinian corals, they have differentiated polyps with different biological functions. This phenomenon is also found amongst many octocorals. The gastrozooids or feeding polyps are dedicated to prey capture and nutrient acquisition, and the dactylozooids or defensive polyps use their powerful cnidocytes to defend the colony. The way these different polyps are organized spatially in a colony depends on species. A common arrangement is one gastrozooid that is surrounded by five to fifteen dactylozooids, the latter being much longer and thinner. Lace corals are shades of purple, pink or red and much more colorful than fire corals, which are typically yellow-colored.
The difficulty surrounding the husbandry of these corals is, similar to the other animals discussed here, most likely stems from their feeding habits. Although members of the Milleporidae host symbiotic dinoflagellates to support their metabolism, Stylasterids such as Distichopora spp. do not. This causes them to quickly deteriorate in the average aquarium, their bare corallum quickly changing into a shade of green or brown due to algal fouling. I have had some fortunate experiences with several purple Distichopora specimens, of which I have not been able to determine their exact species. These specimens were introduced in good condition, and have remained healthy ever since their introduction in the system about a year ago. Their whitish, calcifying tips and continuous polyp expansion are indicators of health. Dactylozooids can be seen macroscopically. I also introduced a larger, blue specimen that was already deteriorating. Unfortunately, this colony did not recover and slowly died over the course of several months.
Gorgonians (subclass Octocorallia, order Alcyonacea) have become popular ornamentals over the last few years, with the advent of specialized aquarium displays. Their interesting morphologies and colors attract the attention of many aquarists and hobbyists. At this moment, gorgonians are classified into three suborders within the Alcyonacea order; the Calcaxonia, Scleraxonia, and Holaxonia. Although they are related to soft corals, and to a lesser degree scleractinian corals, their body plan is quite different. The inner core of their skeleton houses a proteinaceous rod composed of gorgonin and collagen fibers that provide the colony with stability (Fabricius and Alderslade 2001). Members of the Calcaxonia have rods that are reinforced with aragonite, a form of calcium carbonate or limestone that makes up the skeleton of scleractinian corals. The Scleraxonia suborder contains species that produce sclerites-tiny needles made from calcite, another form of calcium carbonate-that provide strength. The Holaxonia are characterized by a hollow inner core.
Many aquarists have been successful at maintaining gorgonians from the Caribbean, including Plexaura and Plexaurella spp. (Holaxonia). This success is most likely due to the presence of zooxanthellae, which is reflected in their brown coloration. Other, more colorful azooxanthellate gorgonians, however, have been proven far more difficult to maintain for prolonged time. Examples are species from the genera Menella, Swiftia and Guaiagorgia (Holaxonia), and Diodogorgia (Scleraxonia).
Gorgonian octocorals feed on a diverse array of particles, including zooplankton (e.g. copepods, rotifers), phytoplankton (e.g. diatom and dinoflagellate algae), protists (various microorganisms), protozoa (e.g. flagellates, ciliates) and detritus (particulate organic matter or POM). These particles range from approximately 1 to 2,000 μm in size, which underscores the importance of pico-, nano-, micro- and mesoplankton in the diet of azooxanthellate corals. Feeding preferences may greatly vary between species, where polyp size (diameter) may not be a good indicator of feeding preference, although it will determine maximum prey size a given species can ingest. Azooxanthellate gorgonians require intensive feeding with a wide variety of particles to meet their respiratory demands, including bacteria, protozoa, phyto- and zooplankton. Rotifers (Brachionus plicatilis), Artemia nauplii and small-sized copepods may be accepted by these corals, as well as various algae (diatoms and dinoflagellates).
In the wild, predation on zooplankton by corals is often quite limited due to low zooplankton abundance (Palardy et al. 2006; Sebens et al. 1996, 1998). However, experiments have shown that feeding rates can be enhanced by providing high concentrations of zooplankton in the aquarium, with an approximate linear relationship between plankton concentration and feeding rate (Clayton and Lasker 1982; Lasker 1982; Lewis 1992; Ferrier-Pagès et al. 1998, 2003; Houlbrèque et al. 2004; Wijgerde et al. 2011). Although zooplankton concentrations on reefs are quite low, prey is available constantly. In addition, crepuscular zooplankton migration leads to elevated zooplankton concentrations at night, which can increase fivefold (Yahel et al. 2005). From this it becomes clear that small amounts of food items should be available throughout the day and night. This may be a major part of the successes obtained with DyMiCo.
Several gorgonian species, including Guaiagorgia sp., were introduced in one of the DyMiCo systems. All colonies exhibited regular polyp expansion and clearly responded to feedings. Growth was discernible although growth rates were not determined. At this time, it seems these azooxanthellate corals can be succesfully maintained in aquaria equipped with DyMiCo.
The successful husbandry of crinoids has been an aspiration for many aquarists, and so far the results have been dismal. To the best of my knowledge, there are no reports of crinoids surviving for prolonged time in closed systems, let alone reproducing. It is evident that in the average aquarium, these specialized animals do not encounter prey items in sufficient quantities to survive. In most cases, these animals slowly lose their arms until only the center part or calyx of the body remains. This, in turn, slowly disintegrates until only bony fragments called ossicles are left.
Crinoids are true suspension feeders and grab small food particles from the water by using their podia or tube feet. The podia secrete mucus to which food items adhere, after which they are propelled to the so-called ambulacral groove. These food grooves run along the animal’s arms and are lined with cilia, tiny beating hair-like structures which transport mucus-imbedded food particles to the central mouth. Crinoids predominantly feed on nano- and microplankton, including unicellular organisms (e.g. foraminiferans), phytoplankton (e.g. diatoms) and zooplankton (e.g. rotifers, mollusk larvae and copepods) (Rutman and Fishelson 1969; Kitazawa et al. 2007).
Three unidentified crinoids (order Comatulida) were introduced in one of the systems, after which their behavior and survival were recorded over a one-year period. These echinoderms seemed to thrive and had their arms extended throughout the day. At this time, they remain in good condition.
Next to the observations described above, there have been other interesting developments. Azooxanthellate octocorals, e.g. Dendronephthya and Scleronephthya spp., seem to be promising candidates for future testing in DyMiCo. A few months ago, an almost completely withered red-colored Scleronephthya sp. was introduced in one of the systems. It slowly recovered into several small colonies with clearly expanded polyps. Although these results are preliminary, these octocorals may thrive provided that sufficient feeding with (live) phytoplankton cultures is maintained, as they are predominantly herbivorous (Fabricius 2005).
Although many aquarists have witnessed coral spawning and release of larvae (planula) in closed systems, this is usually unpredictable and sparse. Several months after the introduction of several small-sized Pocillopora damicornis colonies, a well-known scleractinian coral, I was happy to witness countless offspring on the system walls. These new colonies, also referred to as recruits, arose from the settlement of larvae that were released by the corals after the lights went out. The larvae, after having chosen a suitable spot, metamorphose into a so-called primary polyp that start dividing and grow their own colony. Although I was not able to determine whether these new recruits originated through self-fertilization or polyp bailout, the survival of planula in large numbers is promising.
On the system walls, many unidentified sponges, polychaete tube worms, and other life started growing after several months, similar to what one might find in a dark filtration compartment. On the live rock that was introduced, different species of macro algae and Porites corals developed. Various unidentified species of nudibranchs were found as hitchhikers on the rock. Although these phenomena are common even in heavily skimmed Berlin systems, the explosion of life in these aquaria is remarkable.
It is exciting to witness the health and growth of marine invertebrates which have proven to be notoriously difficult to maintain in aquaria. Their progress in DyMiCo systems will be monitored in the future, and hopefully these organisms will continue to grow and flourish. Perhaps, they may someday even reproduce sexually. Despite the complete lack of water changes, water quality of the DyMiCo systems remained high, adding to the environmentally friendly nature of DyMiCo. Although water analysis has indicated that supplementation of some trace elements including strontium may be required, most water parameters remained close to optimal values.
It is not yet clear whether this technology functions properly in home aquaria, but if it does, it could potentially change the future of the marine aquarium hobby. In that case, the spectrum of marine invertebrates that can be maintained at home would be drastically increased. I would like to end part two of this article by expressing the hope that within several years, we will have mastered the husbandry and reproduction of many (in)vertebrates that are relevant to us as aquarists, hobbyists, scientists and breeders. This will prevent us from taking endangered species from their native habitats, which will relieve some of the pressure on wild populations.
I would like to thank Peter Henkemans at EcoDeco and Michaël Laterveer at Bluelinked for their support during the writing of this two-part article.
Tim Wijgerde, M.Sc. is a Ph.D. candidate at Aquaculture and Fisheries, Department of Animal Sciences, Wageningen University. His research focuses on the heterotrophy of scleractinian corals. To find out more about the Dynamic Mineral Control technology, visit the official website at www.ecodeco.eu.
Using Data Science and Artificial Intelligence in Your Tech Company
As a tech company, you will always be looking for ways to develop. Using data science and artificial intelligence can be useful for this type of growth. While they share some similarities, there are also some differences between the two. You may be surprised to hear about the amazing benefits that AI offers for startups, especially those in the tech sector.
You may have heard artificial intelligence being referred to as AI in countless movies and TV shows. In real life, it’s used for creating improvement rather than turning on humanity, as it is so often shown to be doing on screen, even though this makes interesting viewing.
AI has many uses, such as helping with translations, analyzing complex information and decision-making. It also has the ability to learn and therefore improve and adapt.
Rodrigo Liang is CEO of SambaNova, which provides both hardware and software to businesses for the purpose of analyzing data. While this can be classed as data science, one difference is that data science tends to use a predictive model to make its analysis, while AI can be capable of analyzing based on learned knowledge and facts. This information may not have been programmed, which is why AI can be more precise and take factors into account that weren’t previously considered.
Data science covers a broad range of techniques, including statistics, design and development. It can be used to achieve quick mathematical calculations and find hidden patterns and trends in the data it analyzes, but it needs an element of human intervention. One difference is that using AI can remove the need for human input as it learns and develops.
The programming for data science relies on already having statistics and predictive trends to work with. This information can then be used to find patterns and other details that might not be immediately obvious without hours, days or even weeks of human analysis.
Both AI and data science can be used interchangeably depending on what is required, and they can complement each other.
The benefits to your tech company
One way that AI can be used to benefit your tech company is to carry out risk analysis. Otherwise, this can be an expensive task, particularly in the event of human error. It also saves time, as AI can process and analyze large amounts of information much quicker than a person can. Therefore, although the initial outlay might be high, the savings to your business will more than compensate for this. One example of this is fraud detection, which in some cases could be enough to force a business to close if it’s not caught or prevented in time.
AI can also help with translating different languages. Most businesses rely on trading with customers and other businesses around the world, but the language barrier can make that more difficult. If you need to meet with or send emails to clients, or create content for speakers of other languages, hiring a translator can be expensive. It’s also risky if you’re dealing with sensitive information. That’s why AI is so popular for translating. It not only saves money but also inspires trust in your company, as the information is kept secure.
Data science can be used to spot trends and patterns in your business. This is useful if you need to cut costs in areas that are losing money for your business, or if you need to focus your attention on more successful aspects to boost these further. No successful tech company will want to continue spending money on the parts of it that aren’t cost-efficient. AI can work well with data science here, by thinking logically to find a viable solution and make improvements.
Although AI can translate human facial expressions, tone of voice and body languages to interpret human emotion, the ability to find solutions using logic can be an advantage to your tech company. While you and your employees may try to operate fairly and make the right decisions, it’s difficult to be completely impartial. We have our own thoughts and opinions, and these can shape our decisions, whether or not we want them to.
When it comes to repetition in the workplace, nobody wants to be stuck doing the same thing repeatedly. It’s no good for the morale of your employees, and they will eventually leave if they don’t feel like they’re getting job satisfaction. It may feel like using data science and AI in your tech company will kill off jobs for humans. However, it’s just as likely that they can be better placed doing other less menial tasks within your company. If using these technologies results in fewer financial losses and more gains, then there is no reason why employees can’t be relocated elsewhere in the company on more appealing tasks.
AI Offers Great Advantages for Tech Startups
AI and data science can be great for your tech company, removing or lowering risk, increasing profits, and generally helping you run your company with fewer problems, and with fewer job losses than you might think. Any initial costs will usually be recuperated.
The post Using Data Science and Artificial Intelligence in Your Tech Company appeared first on SmartData Collective.
Tech Regulatory Overhaul Series: The Glass-Steagall Act for the Internet
Following our introductory blog post on the bills introduced in the House to target the most successful tech companies in the U.S., this next blog post in this series will offer an analysis of the bill introduced by Representative Jayapal with the aim to engage in industrial organization and mandate the structural separation of these designated companies.
Representative Jayapal introduced the ‘Ending Platform Monopolies Act’ with the aim of eliminating what some policy makers have classified as ‘conflicts of interest’ in the digital space. In reality, this bill is inspired by the Glass-Steagall Act and represents an attack on multi-sided business models that have succeeded by providing consumers a variety of integrated services. In other words, this bill wants to break up the most successful digital service providers in the U.S., and harm consumers. This is the main reason why some commentators have referred to it as the Glass-Steagall Act for the Internet.
Back in 1933, Congress passed the Glass-Steagall legislation, which consisted of a series of laws imposing a separation of banks’ business lines, specifically commercial and investment banking services. Inspired by this legislation, Representative Jayapal’s bill considers that online platforms may have ‘conflicts of interest’ among the services they provide to consumers, and has crafted an approach that will impose a structural separation on a selected group of tech companies to eliminate such conflicts.
What is the problem with this bill? The main problem is that policy makers have not really analyzed how this legislation would impact consumers in the real world, in addition to being discriminatory and contrary to market economy principles.
It is well known that digital service providers often operate under business models that, by design, offer multiple and diverse services to consumers. For example, MacBook users typically take advantage of the Apple App Store services, or Amazon Prime subscribers enjoy Prime delivery for both products acquired from Amazon directly as well as from third party sellers that operate in their marketplace. LinkedIn users can link their accounts to Skype services, and consumers enjoy seeing a map of the locations they searched for as part of their queries’ results. The user centric business models that have improved users’ experience are what the bill considers to be a ‘conflict of interest’ worth tackling.
Ironically, this bill only considers that these so-called ‘conflicts of interest’ are only worrisome in the digital space, but not in the offline world. So whereas a brick and mortar supermarket that sells third party products and private label products in its store does not raise any concerns, it would in the online space according to this bill. But the cynicism goes even further, because the reality is that this bill won’t be applicable to all online services, and thus, online supermarkets that sell private labels and third party products online won’t be considered troublesome. The reality is that this bill doesn’t tackle what has been considered as ‘conflicts of interest’ but actually would break up a selected group of companies, irrespective of whether this designation is discriminatory, or whether it makes sense or not from a market economy and consumer perspective.
In short, the ‘conflict of interest’ dilemma expressed in the bill is nothing but a shield to justify the imposition of structural remedies to a handful of companies without having to prove harm to consumers that typically characterizes antitrust enforcement.
The legislative classification of the violations included in this bill is no less controversial. The bill establishes that a violation of the act will constitute an unfair method of competition under section 5 of the Federal Trade Commission Act (FTC Act). Section 5 of the FTC Act has been a longstanding unclear provision that has not been exempt from controversy.
Back in 2015, the FTC issued a statement in an effort to clarify what constitutes an ‘unfair method of competition’. In such a statement, the FTC recognized that Congress “[…] left the development of Section 5 to the Federal Trade Commission as an expert administrative body, which would apply the statute on a flexible case-by-case basis, subject to judicial review […].”
The statement also clarified that “the Commission is less likely to challenge an act or practice as an unfair method of competition on a standalone basis if enforcement of the Sherman or Clayton Act is sufficient to address the competitive harm arising from the act or practice.” So this bill introduces an exemption to the current way of enforcing section 5 of the FTC Act, and it remains to be seen whether, if approved, it will have a further negative impact on the agency’s ability to litigate section 5 cases. It is foreseeable that the explicit definition of an ‘unfair method of competition’ as determined in Rep. Jayapal’s bill will weaken the agency’s ability to obtain deference from courts when litigating other section 5 cases that have not been explicitly defined. Not to mention, it renders the FTC’s statement outdated, since Congress is now defining what section 5 of the FTC Act means.
In conclusion, this bill is a discriminatory effort to avoid competition enforcement and break up designated companies regardless of whether as a result consumers and the economy would be better off or not. As a spillover effect, this bill is likely to weaken the FTC’s authority to identify and pursue section 5 cases beyond what is defined by Rep. Jayapal’s bill, decreasing the agency’s competence to win cases against businesses’ conduct that may have a real negative impact on consumers. In essence, this bill will punish consumers and antitrust institutional design, which are the opposite effects of what members of the House are seeking to achieve by introducing the legislation being analyzed in this series of blog posts.
The post Tech Regulatory Overhaul Series: The Glass-Steagall Act for the Internet appeared first on Disruptive Competition Project.
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